DBMS > Brytlyt vs. Drizzle vs. Splice Machine
System Properties Comparison Brytlyt vs. Drizzle vs. Splice Machine
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|Editorial information provided by DB-Engines|
|Name||Brytlyt Xexclude from comparison||Drizzle Xexclude from comparison||Splice Machine Xexclude from comparison|
|Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.|
|Description||Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL||MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.||Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark|
|Primary database model||Relational DBMS||Relational DBMS||Relational DBMS|
|Developer||Brytlyt||Drizzle project, originally started by Brian Aker||Splice Machine|
|Current release||0.9, October 2016||7.2.4, September 2012||3.1, March 2021|
|License Commercial or Open Source||commercial||Open Source GNU GPL||Open Source AGPL 3.0, commercial license available|
|Cloud-based only Only available as a cloud service||no||no||no|
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|Implementation language||C, C++ and CUDA||C++||Java|
|Server operating systems||Linux|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||yes specific XML-type available, but no XML query functionality.|
|SQL Support of SQL||yes||yes with proprietary extensions||yes|
|APIs and other access methods||ADO.NET|
native C library
streaming API for large objects
Native Spark Datasource
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||user defined functions in PL/pgSQL||no||yes Java|
|Triggers||yes||no hooks for callbacks inside the server can be used.||yes|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Shared Nothhing Auto-Sharding, Columnar Partitioning|
|Replication methods Methods for redundantly storing data on multiple nodes||Source-replica replication||Multi-source replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no||Yes, via Full Spark Integration|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||yes||yes||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID||ACID|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes, multi-version concurrency control (MVCC)|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes|
|User concepts Access control||fine grained access rights according to SQL-standard||Pluggable authentication mechanisms e.g. LDAP, HTTP||Access rights for users, groups and roles according to SQL-standard|
|More information provided by the system vendor|
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