Rust vs. C: performance and security in low-level programming (2023)

According to Stack Overflow Developer Survey 2020, Rust is the most popular programming language. It won the title for the fifth year in a row, and the good news doesn't stop there. Also in 2020, the Linux kernel developers proposed including Rust in the Linux kernel originally written in C. More recently, Facebook joined the Rust Foundation, an organization that promotes the development of the Rust language with the intention of helping it become popular.

Given all of this, we decided to see if Rust could replace C inLow-level network programmingto ensure greater security without sacrificing high performance. For usproof of concept, we chose the DPDK library because it is used to write user-space applications for packet processing where performance is a critical factor.

Rust as a system programming language

Rust was created to providehigh performance, comparable to C and C++, with a strong focus on code security. C compilers don't really care about security. This means that programmers must be careful not to write a program that causes memory violations or data races.

In Rust, most of these issues are caught during the build process. You can write code in two different modes: Safe Rust, which imposes additional restrictions on the programmer (e.g. object property management), but ensures that the code works correctly. The other mode is insecure Rust, which gives the programmer more autonomy (e.g. it can work with C-like pointers), but the code can break. For these reasons, Rust is an excellent choice for programming systems that require high performance and security.

Rust vs. C: performance and security in low-level programming (1)

C libraries in Rust

Many projects related to low-level systems, such as operating systems, game engines, and network applications, are written in C or C++. This is mainly because there has never been a real alternative that guarantees high performance and easy access to storage and operating system features.

Today Rust is seen as an alternative, although rewriting an entire project if we want to use this language would break most budgets. Luckily we don't have to. Rust supports calling C functions from Rust code with no additional performance overhead.

Rust vs. C: performance and security in low-level programming (2)

Suppose we have a simple library written in C:

#contain <stdio.h>#contain <stdlib.h>Structure CStruct { int32_ta ;};Structure CStruct *init_struct(int32_ta ) { Structure CStruct *s= malloc(size of(*s)); What happened if (s!= NULL)s->a =a ; Returnss;}file free_struct(Structure CStruct *s) { for free(s);}

We can create bindings to these functions and structures and use them like this:

#[repr(C)]Structure CStruct {a : i32,}extern "C" { fn init_struct(a : i32) -> *Period CStruct; fn free_struct(s: *Period CStruct);}fn a director() { unsure { leavings= init_struct(5); What happened if !s.is zero() { press!("s->a = {}", (*s).a ); } free_struct(s); }}

These links are easy to write. There are even special tools (the remaining binding) that you can generate automatically. They are unfortunately very raw and requireunsureBlocks to use them, so we can't take full advantage of Rust's features. In this case, the programmer must check whether the mapping was successful (sis not null) before it is dereferenced and an array is accessed. We could theoretically ignore thatinit_structmay return and read nullptr in some casess.awithout this test. This would work most of the time, but sometimes it would fail at runtime - that's why it's not safe in Rust. We must also remember to free memory - or risk a memory leak. However, these bindings are a good first step towards a more decent API that would enforce correct use of this library. The code above can be grouped as follows:

Structure remainderstructure {cstr: *Period CStruct,}imply remainderstructure { fn Novo(a : i32) -> Result<Auto, ()> { // Use raw bindings to create the structure leavingcstr= unsure {init_struct(a )}; // returns Err if the build failed, or Ok if the build was successful What happened ifcstr.is zero() { Returns err(()); } OK(remainderstructure {cstr}) } fn get one(&Auto) -> i32 { // At this point we know that self.cstr is not null// so it's ok to just dereference unsure {(*Auto.cstr).a } }}imply Drop Pro remainderstructure { fn drop(&Period Auto) { // Freeing the structure doesn't fail unsure {free_struct(Auto.cstr)}; }}// You don't have to remember to free the structure - it will be freed when it's out of scopefn a director() -> Result<(), ()> { // We need to handle the case where RustStruct::new fails and// returned Err so we can't use mismatched s leavings= remainderstructure::Novo(5)?; press!("s->a = {}",s.get one()); OK(())}

unsureBlocks are moved into the library code, that is, ina director()We can use the secure Rust API.

DPDK in Rust

allow packet processing in user space,DPDKis a library used for programming high-performance network applications. DPDK is written in C, so using it with Rust without a properly prepared API is inconvenient and unsafe.

We're not the first to try to create bindings for DPDK in Rust. We decided to base our API on another project—ANLAB-KAIST/rust-dpdk. This project uses bindgen when compiling code to generate bindings for the specified DPDK version.

This makes updating the API to the latest DPDK version easy. Also, much of the high-level API was already well-written, so we didn't have to write it from scratch. Finally, we just added a few features to this library and fixed some issues. Our final version of this API is here:codylime/rust-dpdk.

The interface for communicating with the DPDK is designed in such a way that the programmer does not have to remember any non-obvious dependencies that can lead to errors in DPDK applications. Below we present some examples of the API with the corresponding code in C.

(Video) coding in c until my program is unsafe

EAL initialization

{ intret= rte_eal_init(Argc,argv);Argc-=ret;argv+=ret; // Parse application-specific arguments // ... rte_eal_cleanup();}
{ // args - The command line argument leavingreal= Eal::Novo(&Periodargument)?; // Parse each specific argument // Parse application-specific arguments // ...} // eal.drop() calls rte_eal_cleanup() and others

Most DPDK functions can only be called after EAL initialization. In Rust this was solved by creating an instance of aEalStructure. This framework provides more functionality in your methods. In addition, thanks to the participation of the EAL in the structure, it is not necessary to carry out a cleanup at the end of the program. It will be called automatically when therealstructure falls.

Ethdev and RX/TX queue initialization

{ RTE_ETH_FOREACH_DEV(ported) { // Configure the device and create 1 RX and 1 TX queue rte_eth_dev_configure(ported, 1, 1, &port_config); // configure queues rte_eth_rx_queue_setup(ported, 0,nb_rxd, rte_eth_dev_socket_id(ported), &rxq_config,pktmbuf_pool); rte_eth_tx_queue_setup(ported, 0,nb_txd, rte_eth_dev_socket_id(ported), &txq_config); rte_eth_dev_start(ported); rte_eth_promiscuous_enable(ported); } // ... // deinitialization RTE_ETH_FOREACH_DEV(ported) { rte_eth_dev_stop(ported); rte_eth_dev_close(ported); }}
{ leavinguninit_ports=real.doors()?; leavingdoors_with_queues=uninit_ports.into_iter().Map(|uninit_port| { // Configure the device, create and configure 1 RX and 1 TX queue leaving (porta, (rxqs,Many Thanks)) =uninit_port.Start(1, 1, none);porta.begin().unpacking();porta.set_promiscuous(real); (porta, (rxqs,Many Thanks)) }).collect::<vec<_>>(); // ...} // port.drop() chama rte_eth_dev_stop() und rte_eth_dev_close()

In DPDK applications, ethdev is normally initialized once at program startup. Multiple queues can be passed to the configuration at startup. in rust,real.ports()returns a list of uninitialized ports, which can later be initialized separately, producing a structure corresponding to the initialized port and lists of RX and TX queues. vocationreal.ports()a second time causes a runtime error, preventing a single device from booting multiple times.

Our Rust API simplifies initialization - a large part of the DPDK function calls are hidden in theuninit_port.init()Implementation. Of course, this means we don't have much power when configuring devices and queues in Rust, but we get a simpler implementation.

RX/TX queues

{ Structure rte_mbuf *pkts_burst[MAX_PKT_BURST]; uint16_tnb_recv= rte_eth_rx_burst(ported,line identifier,pkts_burst,MAX_PKT_BURST); // ... uint16_tnb_sent= rte_eth_tx_burst(ported,line identifier,pkts_burst,MAX_PKT_BURST);}
{ leaving PeriodPkt= ArrayVec::<Package<TestPriv>, MAX_PKT_BURST>::Novo(); leavingnb_recv=rx_queue.Reception(&PeriodPkt); // ... leavingnb_sent=tx_queue.tx(&PeriodPkt);}

Each queue is associated with an ethdev, so it would be easier to work with queues than devices when sending and receiving packets. In Rust we have specific structures for RX and TX queues, so working with them is easier.

Also, the RX and TX queues in DPDK are not thread-safe, so the frameworks are designed in such a way that any attempt to use them in multiple threads will result in a compile-time error.

Change in package content

{ Structure rte_ether_hdr *eth= rte_pktmbuf_mtod(Package, Structure rte_ether_hdr *); Structure rte_ether_addrgossip= (Structure rte_ether_addr) { .addr_bytes= {1, 2, 3, 4, 5, 6} }; Structure rte_ether_addrdmac= (Structure rte_ether_addr) { .addr_bytes= {6, 5, 4, 3, 2, 1} }; memcpy(&eth->d_adr.addr_bytes, &dmac.addr_bytes, size of(dmac.addr_bytes)); memcpy(&eth->s_adr.addr_bytes, &gossip.addr_bytes, size of(gossip.addr_bytes));}
{ leaving Periodeth= Spiel Quadro-Ethernet::new_checked(Package.data_mut())?;eth.set_src_addr(Ethernet-Address([1, 2, 3, 4, 5, 6]));eth.set_dst_addr(Ethernet-Address([6, 5, 4, 3, 2, 1]));}

By using Rust, we can easily add functionality written by someone else by simply adding box names to the Cargo.toml file. So in case of packet data changes (e.g. header change) we can just use external libraries. We tested and compared several open source libraries - conclusions and performance tests are below.

several topics

{ RTE_LCORE_FOREACH_WORKER(lcore_id) { rte_eal_remote_launch(lcore_function,Private,lcore_id); }}
{ dpdk::fio::to reach(|to reach| { Prolcorenoreal.lcores() {lcore.throw(to reach, |Private| lcore_function(Private)); } })?;}

The DPDK allows us to launch code on a specific logical core. We combine Rust thread management with DPDK Lcore management. Thanks to this, the API allows you to create threads in specific colors while providing the convenience and security that Rust threads are known for.

Example: l2fwd

To test the Rust API, we implemented a DPDK fonts application in Rust. We decided to test l2fwd (l2fwd description). It's a simple application that can receive packets from a port, change MAC addresses in an Ethernet header, and forward the packets to another port. Here you can find the source codes ofl2fwd em Cel2fwd in Rost.

>> Discover ourrust development services

Rust vs C: Performance Comparison

We compared the performance of both applications in a bare metal environment with two Intel Xeon Gold 6252 CPUs. l2fwd used a core from the first CPU (NUMA node 0), while theTRex traffic generatorused 16 cores from the other cpu (node ​​NUMA 1). Both applications used local memory of the NUMA node, so they didn't share any resources that could affect performance (e.g. caches, memory).

(Video) This Is How Rust Stops Memory Leaks

Additionally, l2fwd used a single interface of an Intel XXV710 25Gbps Ethernet network adapter connected to NUMA node 0 and an RX and TX queue for traffic management. TRex used a NIC with a 25 Gbps interface connected to NUMA node 1.

The generated traffic consisted of L2 packets with a single IPv4 header and UDP with multiple IP addresses and UDP ports. Added additional data to the end of the packet when testing larger packet sizes. Further details on the subject of the environment can be found in ourRepository.

Rust vs. C: performance and security in low-level programming (3)

Coward. 1 The environment used for testing

We also measured the core utilization during the test. In the main function, l2fwd polls incoming packets in an endless loop. This allowed us to achieve better performance than traditional interrupt packet handling. However, CPU utilization is always around 100%, so measuring actual core utilization is more difficult. We use the method describedon hereto measure CPU usage.

With each loop iteration, l2fwd attempts to read a maximum of 32 packetsrte_eth_rx_burst(). We can calculate the average number of packets received from these calls. If the average value is high, it means that l2fwd is receiving and processing packets on most of the loops. When this value is low, l2fwd usually loops without doing any meaningful work.

overload test

The congestion test sent as much traffic as possible to exceed l2fwd's processing resources. In this case, we wanted to test software performance, knowing that l2fwd would always have something to do.

Rust vs. C: performance and security in low-level programming (4)

Table 1 Rust vs. C: Overload test results

Rust performed significantly worse on this test. Rust l2fwd received about 1.2 fewer packets than C l2fwd and sent fewer packets. We can also see that the average RX burst for Rust l2fwd is max (32) and we get about 24.5 RX burst size for C l2fwd. All of this means that the C implementation is faster overall because it can handle more packets. We believe the main reason for these differences is that handling deleted packages written in Rust is less efficient compared to C.

The drop rate is very high in both applications. The most likely cause is that we were using a single TX queue and it couldn't handle more packets.

It also explains why the C implementation's crash rate is higher than Rust's. Both applications wanted to send more than the TX queue could handle, but C was faster than Rust and attempted to send more packets, resulting in a higher drop rate.

RFC2544

We ran the RFC2544 test on both l2fwd implementations. The results are shown below.

Note that the actual packet sizes sent in the charts consist of the packet data plus an additional 13 bytes added by TRex (preamble and IFG).

Rust vs. C: performance and security in low-level programming (5)

Coward. 2 Throughput comparison between C and Rust [bps].

Rust vs. C: performance and security in low-level programming (6)

Coward. 3 Comparison of productivity C vs Rust [pps]. The bigger the packet, the fewer packets you have to send to reach 25 Gbps. This explains the decrease in pps for larger packets.

Rust vs. C: performance and security in low-level programming (7)

Coward. Comparison of 4C and average Rust latency

(Video) Lecture: Rust vs. C Programming Languages

Rust vs. C: performance and security in low-level programming (8)

Coward. 5 Comparison C with Rust jitter

Rust vs. C: performance and security in low-level programming (9)

Coward. 6 Difference between TRex RX and Rust l2fwd and C l2fwd

During testing, we observed that the average number of packets per RX burst was always less than 2. This means that l2fwd was mostly idle during the test, which explains why the results for C and Rust are so similar. To see visible differences, we would have to test them with more complex applications.

We couldn't get 25Gbps on smaller packages, even though l2fwd was pretty much idle. This can be attributed to a single TX queue not being able to handle all the traffic.

We can also see that there were some tests where Rust performs slightly better than C, even though it performs worse in the overload test. We suspect that the Rust implementation is mostly worse at handling dropped packets, so in the case of RFC2544 where drops are not allowed, we can see that the Rust implementation gives comparable or sometimes better results than C.

Appendix: Package processing libraries

We tested some libraries for package data changes. The tests consisted of modifying the packet data (setting the source and destination MAC addresses and the source IP address to constant values). All testing was done locally on a single machine, so only memory changes made by libraries were tested, not traffic management. Test sources can be found on ourRepository.

Tests compiled with link-time optimizations performed significantly better than those without them, so we compared these two cases.

Etherparse library

Forether parse, we tried different methods of modifying packages:

  • Instead of just changing the required locations, build the package from scratch:

Rust vs. C: performance and security in low-level programming (10)

Coward. 7 link timing optimizations enabled vs disabled using the Etherparse library (build packages from scratch).

  • Using Rust std::io::Cursor which only copies the required memory:

Rust vs. C: performance and security in low-level programming (11)

Coward. 8 Link timing optimizations enabled vs. disabled using the Etherparse library (using std::io::Cursor).

  • Using pure slices instead of cursors:

Rust vs. C: performance and security in low-level programming (12)

Coward. 9 link timing optimizations enabled vs disabled using Etherparse library (using slices).

We compare the assembly instructions generated after link-time optimization in all these cases:

  • Slice Method:

    • 465 asm instructions
    • includes calls to memcpy, memset, malloc
  • Cursor Method:

    • 871 asm instructions, almost twice as long as the slice method. That's why the results in benchmarks are worse than in slices
    • includes calls to memcpy, memset, malloc
  • Create package from scratch:

    (Video) Rust Runs on EVERYTHING, Including the Arduino | Adventures in Embedded Rust Programming

    • 881 asm instructions
    • too much memory manipulation
    • Allocate and free storage space

pnet library

nopnet, In-Place Package Changes:

Rust vs. C: performance and security in low-level programming (13)

Coward. 10 link timing optimizations enabled or disabled using the Pnet library.

Checking the assembly instructions generated after link-time optimizations:

  • 19 asm statements
  • 2 branches

A smoltcp library


nosmoltcp, In-Place Package Changes:

Rust vs. C: performance and security in low-level programming (14)

Coward. 11 link timing optimizations enabled or disabled using the smoltcp library.

Checking the assembly instructions generated after link-time optimizations:

  • 27 asm instructions
  • 5 branches

Conclusions from the performance results

A comparison of all libraries can be found below:

Rust vs. C: performance and security in low-level programming (15)

Coward. 12 Comparison of all libraries with connection time optimization enabled

Rust vs. C: performance and security in low-level programming (16)

Coward. 13 Comparison of all libraries with disabled link time optimization

Without link-time optimizations, pnet and smoltcp are very different, although both modify packages in-place. A possible reason is the poorer implementation of the pnet library, which was more difficult for the compiler to optimize. After enabling link timing optimizations, pnet and smoltcp returned similar timing results, although smoltcp generated more assembler statements and branches than pnet. All of these branches were error checks, so the branch predictor didn't have much trouble optimizing them.

Etherparse generates a lot more assembler instructions than pnet and smoltcp, and it also seems better suited to building packages from scratch than modifying them.

We used smoltcp in the l2fwd implementation because it worked very well with and without link time optimizations.

Check out our other articles on rust:

  • Why is the Rust programming language so popular?
  • Rust vs C++– the main differences between these popular programming languages
  • Rust vs Go– What do you need to know about these programming languages?

final thoughts

Our tests show that replacing C with Rust resulted in performance degradation. An implementation written in Rust achieved about 85% of the performance of C in the overload test, but we still see room for improvement in the implementation of the bindings, which can bring us closer to the performance of C. On the other hand, at the cost of performance loss, we get Rust security controls that make it easier to create secure code. When programming the system, e.g. B. network applications, this is very valuable.

We also used a very simple l2fwd, which is why the RFC2544 results were so close. We can't be sure how Rust would perform in a more demanding scenario. Because of this, in the future we intend to build a complex application in C and Rust using the bindings we have described. This would allow us to do a more detailed performance comparison.

Language developers learned their lesson and developed Rust, a modern alternative to C and C++ that solves many of the problems (e.g. related to memory management and/or multithreaded programming) in programming languages. We are happy that it replaces C and C++ in some use cases.

(Video) Rust vs. C in networking applications

FAQs

Is Rust more secure than C? ›

Well, unlike C, Rust is a safe programming language. But, like C, Rust is an unsafe programming language. More accurately, Rust contains both a safe and unsafe programming language. Rust can be thought of as a combination of two programming languages: Safe Rust and Unsafe Rust.

Is Rust good for low-level programming? ›

Rust is a low-level programming language with direct access to hardware and memory, which makes it a great solution for embedded and bare-metal development. You can use Rust to write operation systems or microcontroller applications.

Does Rust have better performance than C++? ›

Our evaluation shows that the overall performance of Rust is similar to C++, with only minor disadvantage. We also demonstrate that in some Rust routines are slightly faster than the ones of C++.

Is Rust as low-level as C? ›

No. If you can even make comparisons, Rust is slightly lower level than C++. It is easier to write bare-metal Rust, and easier to interface with low-level hardware details. Rust also does not depend on C++.

What is the drawback of Rust? ›

Rust is fast, no doubt. But when it comes to compiling code, then it's a bit slower as compared to its peer languages. The reason for its slow compile time is that its “unit of compilation” is not an individual file, it's instead a whole package (known as a crate).

Should I use Rust instead of C? ›

However, Rust programs also optimize quite well, sometimes better than C. While C is good for writing minimal code on byte-by-byte pointer-by-pointer level, Rust has powerful features for efficiently combining multiple functions or even whole libraries together.

Why is Rust so low FPS? ›

There can be many overlapping causes for poor FPS, but hardware is the number one cause for low FPS. Upgrading your CPU, memory size or Graphics processor can have a MAJOR impact on your FPS and overall game play. If you can afford to go better, do so.

Does Rust use less memory than C++? ›

According to the above, Rust, on average, uses 15% more RAM overall than C, and 10% more RAM above a fixed allowance of 50K. Compared to C++, the results are 5% better without a floor, and 5% worse with one, making the two languages very comparable in this category.

Is Rust good for deep learning? ›

Rust supports real multithreading (unlike Python) and that can potentially make it a good language for building distributed training libraries for training deep learning models.

Why is Rust slower than C? ›

Because C is slower than C. That is, they are compiling C with GCC, but Rust uses LLVM as a backend. Compiling their C code with clang reveals that it is also slightly slower than the C code compiled by GCC, but not faster than Rust.

Why should I use Rust over C++? ›

Rust programming language is similar to C++ but it provides memory safety without using garbage collection. It is aimed at achieving higher performance and better safety than the C++ programming language.

Why carbon instead of Rust? ›

What makes Carbon better suitable than Rust is its introducer keywords and simple grammar. Carbon's unction input parameters are read-only values and the pointers provide indirect access & mutation. The writer can use expressions to name types and the package is the root namespace.

Which is faster C or Rust? ›

C, C++ and Rust are all in the same performance class, meaning that equivalent programs written in these languages and compiled with best in class optimising compilers tend to have indistinguishable performance, statistically speaking. Rust is not faster than C.

Does Google use Rust? ›

Google has begun using Rust in settings where memory safety and performance are key considerations, including in key Android systems. The Rust Core Team recently completed its work to build a new home for Rust: The Rust Foundation.

What can C++ do that Rust cant? ›

C++ has unrestricted, raw union s. Rust doesn't have a similar feature yet. C++ has automatically invoked, user-defined move constructors. In current Rust something is either moved by a shallow memory copy, or is statically forbidden from being moved by the borrow checker.

Why is rust a big problem? ›

Rust reduces product lifespan

If equipment is damaged, more time has to be spent repairing or replacing it, which therefore increases costs. Rust weakens metal by reducing its mass and so after a lot of rusting, the piece of iron may no longer be able to support the weight it once held.

Does rust have future? ›

The future of Rust

Looking at the plethora of benefits that Rust can offer, its popularity will only continue to grow in 2023. Rust solves problems that developers have been facing for years, while still providing the high level of performance that they have come to rely on.

Why is rust not more popular? ›

Rust is too new to have accumulated that much maintenance yet. Often times, language choice for new development is dictated by what libraries and other existing code is out there for the kind of problem you are working on. Rust is too new to have libraries for absolutely everything.

Does Rust need a good CPU? ›

Recommended System Specifications:

CPU: i7-4690K or R5 1600. Graphics Card: GTX 980 or R9 Fury. RAM: 16GB. Storage Space: 20GB.

Does Rust require more RAM? ›

Rust system requirements state that you will need at least 8 GB of RAM. If possible, make sure you have 16 GB of RAM in order to run Rust to its full potential. An Intel Core i7-3770 CPU is required at a minimum to run Rust. Whereas, an AMD Ryzen 5 1600 is recommended in order to run it.

Is Rust good for hardware programming? ›

Rust is an increasingly popular programming language positioned to be the best choice for hardware interfaces. It's often compared to C for its level of abstraction. This article explains how Rust can handle bitwise operations in a number of ways and offers a solution that provides both safety and ease of use.

Is Rust CPU or GPU heavy? ›

Is Rust GPU or CPU intensive? Rust is a CPU-intensive game and has some of the highest hardware requirements in the gaming industry. You will need at least an Intel Core i7-3770 CPU or an AMD FX-9590 CPU to run Rust smoothly.

How much RAM should Rust use? ›

It is roughly 100MB (0.1GB) per player. The RUST.io livemap adds 0.3GB of RAM usage. Looking for a game server host known for brilliant 24/7 customer support and quality hardware?

How much FPS do you need for Rust? ›

Example Rust PC Builds

These builds are designed to provide sufficient computing power for playing Rust at 60+ FPS (or 100+ FPS, where noted) at 1080p, 1440p, or 4K resolution.

Is Rust good for big data? ›

Rust Language Integration to Big Data Solutions!

Rust is a functional programming language that is gaining more space in the market every day because it is designed to be highly safe and performant and a viable alternative to other languages such as C, C++, Java, Google CarbonLang, and Go, and others

Is Rust compilation slow? ›

Rust's compile times are notoriously slow. Rust development was slow enough on my laptop that I finally gave up on mobile computing and bought a desktop with a top-of-the line CPU (12900K). Along the way I switched from Windows to Linux (more on that later) and started using the mold linker, and now… things are OK!

Why Rust is so fast? ›

Rust is fast

Binaries are self-contained, with no external runtime apart from what the OS might provide, and the generated code is meant to perform as well as comparable code written in C or C++.

Is Rust harder to learn than C? ›

Rust is far easier to learn than C++, but as the Recent Rust Developer Survey highlighted, very few people can currently code in Rust proficiently. Employers like B2C2, therefore, are flexible when it comes to hiring.

Should I learn Rust as a data engineer? ›

In summary, Rust might be the best choice for data engineering if speed, performance and reliability are your top priorities, you're working with Apache Arrow, if safety and security are highly prioritized, and when you might want to have rigidly defined data types.

Is Rust good for artificial intelligence? ›

Rust is a powerful and efficient programming language. Although Rust doesn't have a mature ecosystem, the programming language's nature makes it perfect for applications that require speed and efficiency. Rust programmers will find this tutorial useful in getting started with machine learning.

Why is Rust so laggy PC? ›

Low-Performance Hardware

If your computer does not meet the system requirements for Rust, you will experience input lag while playing Rust. The fix for this is getting new hardware that meets the recommended system requirements for Rust.

Can you Go faster than Rust? ›

Rust has the upper hand in delivering output over Go due to its great runtime speed, but it lacks compilation time. On the other hand, Go is better in compilation time but lacks runtime speed. Let's do a comparison of the two from a concurrency perspective.

Is Rust slow burning? ›

It's just like the three items needed for a fire: Fuel (the steel), Heat (any temperature above freezing), and Oxygen (to support the burning or rusting). In fact, rust can be thought of as a slow burn, like charcoal, where rust is the ash.

Can C++ compete Rust? ›

Rust as a C++ alternative

As far as performance goes, Rust is both fast and memory-efficient: with no runtime or garbage collector, it can power performance-critical services, run on embedded devices, and easily integrate with other languages.

What is Rust best suited for? ›

Many consider Rust the best language for building tools suited for today's architectures. The web browser is a good example of an application that requires massive scalability, so it's no surprise that Rust was created by Mozilla, the not-for-profit corporation that developed Firefox.

Why is Rust faster than CPP? ›

Rust can be written faster than C++ due largely to its elaborated semantics and system for preventing undesired behaviors. One of the significant issues with C++ is that avoiding undefined behaviors can be difficult. As a result, it can take longer to write C++ code.

What is future of Rust? ›

Rust is going to be used for many different kinds of applications. It's designed to be as flexible as possible, and with that in mind, a programmer should be able to use it for almost any project. Too many programming languages don't do what they say they will do.

Why is everyone using Rust? ›

In programming, Rust is one of the most loved languages. It is a programming language focused on memory safety, protection, high performance during the processing of large amounts of data, concurrency and a highly efficient compiler.

What is the successor to Rust? ›

Introducing Turbopack, the Rust-based successor to Webpack.

What is a faster language than C? ›

Go. Go, also known as Golang, is a programming language developed by Google. It compiles to Assembly like most of the other languages here, but it has more modern features, simpler syntax, and is easier to write than the long-time leader of fast programming languages, C/C++.

What language is faster than Rust? ›

Zig is faster to type and faster to say than Rust. Though way behind "C", Rust comes out way ahead of Zig, alphabetically. Both are based on LLVM and low-level enough that the user can control almost everything given to LLVM.

How fast is Rust compared to Python? ›

But what puts Rust on a different level is that it's nearly as fast as C and C++, but without the overhead. It took Rust 4.6 microseconds and Python 8.6 microseconds to perform similar operations on the same machine without any optimization techniques, meaning it took Python almost twice as long as Rust.

Does Amazon use Rust? ›

We use Rust to deliver services such as Amazon Simple Storage Service (Amazon S3), Amazon Elastic Compute Cloud (Amazon EC2), Amazon CloudFront, and more.

Does Facebook use Rust? ›

The best programming languages

It joined the Rust Foundation in April 2021 as a platinum member with AWS, Google, Huawei, Microsoft and Mozilla. Facebook has used Rust since 2016, a year after version 1.0 of the language arrived.

Is Microsoft adopting Rust? ›

Rust is a newer programming language that developers enjoy using and learning, and it's being adopted far across the industry, too. The CTO at Microsoft Azure has called on the industry to pivot away from the C and C++ software development languages and embrace Rust for future projects.

Can C C++ replace Rust? ›

Rust is likely to replace a lot of C and C++ in places where security matters. But it won't replace it all, and it won't do it quickly.

Is Rust the most secure language? ›

According to the Stack Overflow Developer Survey 2022, Rust has been the most-loved language for seven straight years. Rust boasts a unique security model, which promises memory safety and concurrency safety, while providing the performance of C/C++.

Is Rust really secure? ›

Rust is what's known as a “memory-safe” language because it's designed to make it impossible for a program to pull unintended data from a computer's memory accidentally.

Can C++ be as safe as Rust? ›

Essentially, to avoid the memory-safety vs. speed trade-off, C++ leaves memory safety to the developer, whereas Rust has inherent memory safety bounds that can be lifted with `unsafe` code. The Rust model for memory safety is a clear reason for selecting Rust, in case you feel memory safety is your problem in C++.

Is Rust more secure than Python? ›

Features. If you consider the features of each language, Rust has more intuitive and distinct features than Python. As discussed earlier, Rust is memory and thread safer than Python. Rust programs are more efficient than Python without garbage collection and run time.

Does Rust have a future? ›

With both developers and major technology brands recognizing Rust's potential, it's set to be one of the most used and popular programming languages in 2023 (and beyond).

What is the safest programming language? ›

  • JavaScript. JavaScript empowers designers to utilize any code when guests visit the site. ...
  • C. C is best for reverse engineering and finding openings. ...
  • Python. Python empowers software engineers to mechanize errands and manage malware research. ...
  • C++ ...
  • SQL for Cybersecurity. ...
  • PHP. ...
  • Shell Scripting. ...
  • HTML.
Jan 15, 2022

Can Rust leak memory? ›

We can see that Rust allows memory leaks by using Rc<T> and RefCell<T> : it's possible to create references where items refer to each other in a cycle. This creates memory leaks because the reference count of each item in the cycle will never reach 0, and the values will never be dropped.

Do people hack on Rust? ›

Since the game is in such early development, an anti-cheat/constant monitor is not implemented, so hackers are rather common even on the official servers (unfortunately). Tip: Most, if not all, hackers are still susceptible to death. If you encounter a hacker, you are advised to log out or secure yourself.

Is Rust more secure than Golang? ›

Rust's heavy emphasis on preventing memory-related security vulnerabilities means programmers have to go out of their way to perform tasks that would be simpler in other languages, including Go. However, Go isn't insecure. Rust just happens to be king for memory safety.

What makes Rust safer than C++? ›

What separates Rust from C and C++ is its strong safety guarantees. Unless explicitly opted-out of through usage of the “unsafe” keyword, Rust is completely memory safe, meaning that the issues we illustrated in the previous post are impossible to express.

Will Rust take over data engineering? ›

Will Rust Be the Programming Language for Data Engineers? Rust is a multi-use language and gets the job done for many problems of a data engineer. But the data engineering space is dominated by Python (and SQL) and will stay that way for the foreseeable future. There is no "until people fully move into Rust".

Is Rust good for cryptography? ›

The programming language Rust [1] is becoming more and more popular and is increasingly used for cryptography. In Rust's favour is the fact that the language promises very secure memory management, making errors such as buffer overflows and use-after-free less likely.

Is Rust future proof? ›

Rust is the future's programming language. It is also the most popular and one of the highest paying languages in the world. It enables anyone to create dependable and efficient software. It combines the speed and low-level access of languages such as C/C++ with the memory security of modern languages.

Videos

1. Best Programming Language | John Carmack and Lex Fridman
(Lex Clips)
2. Rust Is Coming to The Linux Kernel and I'm Not Sure How to Feel
(Low Level Learning)
3. Why You Should NOT Learn Rust!
(Let's Get Rusty)
4. Why companies are migrating from C++ to Rust
(Let's Get Rusty)
5. Python Vs Rust: Which Is Better And Why? | Rust & Python Programming Beginners Guide | Simplilearn
(Simplilearn)
6. Experienced C++ Developers Tell the Truth in 2021
(Stefan Mischook)

References

Top Articles
Latest Posts
Article information

Author: Amb. Frankie Simonis

Last Updated: 06/29/2023

Views: 6532

Rating: 4.6 / 5 (76 voted)

Reviews: 83% of readers found this page helpful

Author information

Name: Amb. Frankie Simonis

Birthday: 1998-02-19

Address: 64841 Delmar Isle, North Wiley, OR 74073

Phone: +17844167847676

Job: Forward IT Agent

Hobby: LARPing, Kitesurfing, Sewing, Digital arts, Sand art, Gardening, Dance

Introduction: My name is Amb. Frankie Simonis, I am a hilarious, enchanting, energetic, cooperative, innocent, cute, joyous person who loves writing and wants to share my knowledge and understanding with you.