A high-performance, concurrent, compressing drop-in replacement engine for MongoDB built on Fractal Tree indexes.
TokuMX is a high-performance distribution of MongoDB that replaces its default storage engine with Tokutek's Fractal Tree indexing technology. It solves performance and scalability issues in large MongoDB deployments by offering faster writes, built-in compression, and concurrent access while maintaining compatibility with MongoDB's API and drivers.
Database administrators and developers running MongoDB at scale who need improved write performance, reduced storage footprint, and better concurrency without changing their application code.
Developers choose TokuMX because it provides a drop-in replacement for MongoDB with significant performance enhancements, built-in compression, and transactional semantics, all while maintaining compatibility with existing MongoDB tools and drivers.
TokuMX is a high-performance, concurrent, compressing, drop-in replacement engine for MongoDB | Issue tracker: https://tokutek.atlassian.net/browse/MX/ |
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Uses Fractal Tree indexing to achieve faster write operations and reduced I/O on large datasets, as shown in iibench benchmarks linked in the README.
Implements document-level locking for concurrent read/write access to collections, improving scalability under load, per sysbench results.
Compresses all data and indexes by default, significantly reducing storage space and costs without extra configuration, as documented in compression resources.
Eliminates data and index fragmentation, removing the need for maintenance operations like compact or repairDatabase, simplifying operations.
Does not support text indexes or geospatial indexing and queries, limiting use for search or location-based applications, as admitted in the README.
Mixed replica sets and sharded clusters with MongoDB nodes are not supported, and multi-statement transactions fail through mongos, complicating hybrid deployments.
Only available for 64-bit Linux systems, with no support for other operating systems or architectures, restricting deployment options.
Requires data export and import from MongoDB, involving downtime or intricate strategies, as migration documentation highlights operational hurdles.