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xxhash is an extremely fast, non-cryptographic hash algorithm that operates at the speed of RAM. Four varieties (XXH32, XXH64, XXH3 64 bits, and XXH3 128 bits) are offered. The library includes these hash algorithms, providing both 32-bit and 64-bit options, as well as the newer XXH3 variants for enhanced performance and versatility. Performance has improved overall with the most recent variant, XXH3, notably for tiny data. A rough evaluation of algorithm’s efficiency on small data sets shows significant speed advantages compared to alternatives. Benchmarking results are often measured on a specific reference system, typically detailing the CPU model, operating system, and compiler used, to provide consistent and comparable performance data.
It does not pass the SMHasher test set with 10 points since it is not a robust cryptographic hash like the SHA family. Since its inception, xxHash has been optimised for speed on contemporary CPUs. The C reference version is the standard implementation, but xxHash is also available in other programming languages, demonstrating its broad support and adaptability.
The xxHash hash algorithm is as quick as memcpy. Algorithms feature faster performance than RAM speed, but are limited by the ram speed limit when input data is not cached. xxHash is portable and works efficiently on both little endian and big endian architectures.
The core source files, xxhash.c and xxhash.h, are BSD licensed, ensuring compatibility and flexibility for integration into various projects.
xxHash is renowned as an extremely fast hash algorithm, engineered to process input data at the very limits of RAM speed. This makes it a top choice for applications where high performance and rapid data throughput are essential. By leveraging the full potential of CPU cache, xxHash achieves superior speed, often outperforming other hash algorithms in both small and large-scale scenarios.
One of the standout features of xxHash is its highly portable hash function, which guarantees that hash values remain consistent across all platforms—including both little and big endian systems. This cross-platform reliability is crucial for distributed systems and client applications that demand identical results regardless of the underlying hardware.
The algorithm is meticulously optimized for small data velocity, delivering better performance on small inputs—a key advantage for hash tables and other data structures that frequently process small keys. Its ability to minimize collisions ensures that hash values are evenly distributed, which is vital for maintaining the efficiency and integrity of hash tables and similar data structures.
For ease of use, xxHash provides a command line utility called xxhsum, which offers a familiar interface similar to md5sum. This utility makes it simple to generate and verify hashes directly from the command line, streamlining integration into build scripts, DevOps pipelines, and other automated workflows.
From a development perspective, xxHash is available as highly portable library files (xxhash.c and xxhash.h), licensed under the BSD license, while the xxhsum utility is GPL licensed. This dual licensing approach offers flexibility for both open-source and proprietary projects. The xxHash source code is finely tuned for performance, utilizing techniques like the GCC specific packed attribute and skip auto detection to maximize speed and evade symbol naming collisions, ensuring smooth integration even in complex codebases.
To further customize the behavior of the library, build modifiers can be set at compilation time. These build modifiers are controlled via the following macros, which can be configured as needed and are typically disabled by default: XXH_FORCE_MEMORY_ACCESS, XXH_FORCE_ALIGN_CHECK, and XXH_NO_INLINE_HINTS. Adjusting these macros at compilation time allows developers to fine-tune performance and compatibility for their specific use case.
xxHash is a fast non-cryptographic hash, intentionally sacrificing cryptographic security in favor of raw processing speed. This makes it ideal for scenarios where speed is paramount and cryptographic resistance is not required, such as checksums, data deduplication, and high-velocity data processing.
When advanced features are needed, xxHash also provides a streaming variant, which allows incremental hashing of data in multiple rounds rather than processing all input at once. This streaming variant offers greater flexibility for applications that handle large or continuously incoming data.
The algorithm’s efficiency is further validated by a comprehensive test suite, which provides a more detailed analysis of its collision resistance and overall performance. Its reference version is widely used as a benchmark for other fast hash algorithms, and its optimized width bandwidth allows it to fully exploit modern CPU architectures.
Thanks to contributions from great contributors, xxHash is available in multiple programming languages, making it accessible to a broad developer audience. It supports both dynamic linking and static allocation, offering flexibility for various deployment models. The design also ensures that functions can be inlined for better performance, and compile time constants are used to further enhance speed.
In summary, xxHash offers a unique blend of high performance, portability, and ease of use. Its extremely fast hash algorithm, robust source code, and broad language support make it an ideal solution for client applications, data structures, and hash tables that require fast, reliable, and consistent hashing at RAM speed limits. Whether you’re building high-performance analytics, real-time systems, or simply need a fast hash for small inputs, xxHash stands out as a superior choice in the world of fast non-cryptographic hash algorithms.
When exploring hashing solutions, it's important to understand the difference between cryptographic and non-cryptographic algorithms. Cryptographic hashes—like SHA-256 or SHA-512—are specifically designed for security use cases, such as password storage or digital signatures, and they emphasize collision resistance to protect sensitive data. Non-cryptographic hashes, such as xxHash, focus instead on speed and efficiency. They are best suited for scenarios like checksums, file integrity checks, or data deduplication where performance is paramount. Using a non-cryptographic algorithm, you can process vast amounts of data much faster than you would with cryptographic solutions. This speed edge makes xxHash an ideal tool for rapid verifications, real-time analytics, or on-the-fly checks for data integrity.
With streaming data or real-time analytics, xxHash can significantly boost performance. Because it's known for its blazing-fast throughput, xxHash helps you stay on top of inbound data without causing bottlenecks. Imagine you're monitoring live sensor feeds, logs, or transaction events—rather than waiting on slower hashing methods, you can use xxHash to verify or tag massive volumes of incoming data in milliseconds. This real-time advantage not only helps you maintain reliable checksums but also allows you to identify anomalies quickly. Whether running a continuous data ingestion pipeline or performing swift message authentication, leveraging xxHash in real-time environments ensures that you meet the demands of modern, data-intensive applications.
Ensuring data integrity is a core reason many developers turn to hashing tools like the xxh-hash generator. You risk corruption or unintended modifications whenever you transfer files across networks or store them in multiple locations. By generating an xxHash checksum, you can quickly verify that your files remain unchanged after a download, upload, or sync. This simple, lightweight strategy is particularly effective for large or frequently accessed files where you need to confirm consistency at scale. You can integrate xxHash checks within your build scripts, backups, or quality assurance processes. That way, whenever a file moves from point A to point B, you'll have robust proof that it arrived safely and without errors.
Big data systems thrive on speed and scalability, and xxHash is a perfect match for high-volume workloads. If you're analyzing petabytes of information in frameworks like Hadoop, Spark, or Kafka, hashing efficiency can substantially impact your overall throughput. xxHash stands out for its low CPU usage and lightning-fast computation, making it an excellent choice for tasks such as partitioning large datasets or filtering out duplicates in data pipelines. When you're facing tight deadlines, real-time dashboards, or batch processing jobs that must complete overnight, xxHash's performance ensures minimal overhead. Its streamlined design allows it to run smoothly within data-intensive clusters, giving you a reliable foundation for faster, more responsive analytics solutions.
Whether you're automating builds or deploying applications at scale, DevOps practices benefit from quick and accurate checks for file consistency. Adding xxHash to your DevOps pipeline allows you to verify integrity across various stages—such as code compilation, artifact generation, and containerization. When you integrate the xxh-hash generator into your CI/CD processes, you'll detect corrupt files and configuration drift early, thus reducing debugging time later on. You can also use xxHash to confirm that dependencies and third-party libraries haven't changed between development and production. This streamlined approach to hashing ensures that every deployment step runs smoothly, giving your team greater confidence in the end-to-end integrity of your software delivery.
xxHash offers multiple variants—namely 32-bit, 64-bit, and the newer 128-bit versions—each designed for particular needs and performance characteristics. If you require a simple, compact checksum for small datasets, xxHash32 might be sufficient. Larger scale projects or systems processing billions of records will often prefer xxHash64 for its balance of speed and lower risk of collisions. Meanwhile, xxHash128 provides an even wider collision space and can be useful if you want a long-term or distributed environment hashing solution. By matching the right xxHash variant to your project's data size and use case, you'll ensure that your checksums perform optimally, keeping your operations both efficient and secure against accidental data corruption.
You'll find xxHash support across a wide range of popular programming languages—from C++ and Java to Python, Go, and Rust. This broad ecosystem lets you incorporate xxHash into virtually any project without reinventing the wheel. Suppose you're building microservices in Go—integrating an xxHash library to check payload integrity between services is typically straightforward. Or if you're developing a machine learning pipeline in Python, you can use the xxh-hash generator as a fast way to tag large datasets. Regardless of the language, you'll benefit from the same hallmark performance and lightweight design. With so many supported implementations, it's easy to create high-velocity solutions that consistently and securely identify data integrity across your entire technical stack.
With data volumes skyrocketing, research into faster, more resilient hashing algorithms exists. As machine learning and AI applications expand, even higher-performance checksums—capable of running on GPUs or specialized hardware—may soon become the norm. You can stay ahead of the curve by watching emerging xxHash variants and related non-cryptographic hashes optimized for parallel computing. Another trend to watch is the integration of hashing tools into container orchestration and serverless environments, ensuring frictionless data verification at scale. By staying up to date on these advancements, you'll be well-positioned to harness the best tools for data integrity, making the most of innovative solutions as they come to market.
Message Digest (hash) allows direct processing of arbitrary length messages using a variety of hashing algorithms to output an fixed length text.
Output is generally referred to as hash values, hash codes, hash amounts, checksums, digest file, digital fingerprint or simply hashes. Generally the length of the output hashes is less than the corresponding length of the input code. Unlike other cryptographic algorithms, the keys have no hash functions.
MD2 is a weak algorithm invented in 1989, still used today in some public key cryptography.
MD5 is an extremely popular hashing algorithm but now has very well known collision issues. - md5 hash generator
The SHA2 group, especially SHA-512, is probably the most easily available highly secure hashing algorithms available. Another modern and highly secure option for password hashing is Argon2 hash generator.
CRC32 is a common algorithm for computing checksums to protect against accidental corruption and changes.
Adler-32 is used as a part of the zlib compression function and is mainly used in a way similar to CRC32, but might be faster than CRCs at a cost of reliability.
Based on the GOST 28147-89 Block Cipher. GOST is a Russian National Standard hashing algorithm that produces 256-bit message digests.
Whirlpool is a standardized, public domain hashing algorithm that produces 512 bit digests.
RIPEMD-128 is a drop-in replacement for the RIPEMD-160 algorithm. It produces 128-bit digests, thus the "128" after the name.
A patent-free algorithm designed in 1995 originally to be optimized for 64-bit DEC Alpha, TIGER today produces fast hashing with security probably on the same order as the SHA2 group or better.
HAVAL is a flexible algorithm that can produce 128, 160, 192, 224, or 256-bit hashes. The number after the HAVAL (e.x. HAVAL128) represents the output size, and the number following the comma (as in HAVAL128,3) represents the "rounds" or "passes" it makes (each pass making it more secure, in theory & some aspects).
This version produces 128-bit digests. SNEFRU-256 also exists but is not currently supported on this site.
Cryptographic hashing has been an integral part of the cybersecurity spectrum. In fact, it is widely used in different technologies including Bitcoin and other cryptocurrency protocols. Supported hashing algorithms:
RIPEMD (RIPE Message Digest) is a family of cryptographic hash functions introduced in 1992, with updated variants released in 1996.
Supported versions include:
RIPEMD-160 remains the most widely deployed due to its balance of security and performance.
Whirlpool is a cryptographic hash function created by Vincent Rijmen (co-author of AES) and Paulo S. L. M. Barreto. First published in 2000, Whirlpool generates a 512-bit digest and is designed for strong security and modern computing architectures.
Tiger is a fast, 64-bit-optimized cryptographic hash function developed in 1995 by Ross Anderson and Eli Biham.
Key characteristics:
Tiger remains known for its high performance on 64-bit processors.
Snefru, designed by Ralph Merkle in 1990 at Xerox PARC, supports 128-bit and 256-bit output sizes.
Its name continues Merkle’s tradition of using Egyptian pharaohs for cipher and hash names (e.g., Khufu, Khafre).
While historically significant, Snefru is no longer considered secure by modern standards.
The GOST hash function, standardized in Russia and CIS countries, produces a 256-bit digest.
Originally defined in GOST R 34.11-94, it was widely used in government and regional cryptographic applications. The CIS version is standardized as GOST 34.311-95.
Adler-32 is a fast checksum algorithm created by Mark Adler in 1995. It is a refinement of the Fletcher checksum and favors speed over high reliability.
Adler-32 is often used in data compression systems like zlib.
A Cyclic Redundancy Check (CRC) is an error-detecting code used widely in networking, storage systems, and communication protocols.
How it works:
CRCs can also support limited error correction.
Common variants: CRC-16, CRC-32, CRC-64.
FNV is a simple, fast non-cryptographic hash function designed for hash tables and lookup operations.
Two main versions exist:
For related bitwise operations, see the Bitwise XNOR calculator - hex, octal, binary,.
Advantages:
Frequently used in compilers, hash tables, and distributed systems.
Developed by Bob Jenkins, this family includes several non-cryptographic hash algorithms optimized for general-purpose hashing:
These hashes are typically used in hash tables, networking stacks, and databases where performance is more important than cryptographic strength.
HAVAL is a cryptographic hash function notable for its variable output length and configurable number of rounds:
Output sizes: 128, 160, 192, 224, 256 bits
Rounds: 3, 4, or 5 passes
However, HAVAL is no longer considered secure:
Because of these vulnerabilities, HAVAL is now considered deprecated for security-sensitive applications.
If you have a procedure with ten parameters, you probably missed some.
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