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DBMS > Rockset vs. Splice Machine vs. STSdb vs. Tarantool

System Properties Comparison Rockset vs. Splice Machine vs. STSdb vs. Tarantool

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Editorial information provided by DB-Engines
NameRockset  Xexclude from comparisonSplice Machine  Xexclude from comparisonSTSdb  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelDocument storeRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Secondary database modelsRelational DBMS
Search engine
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#180  Overall
#31  Document stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Score0.03
Rank#365  Overall
#54  Key-value stores
Score1.63
Rank#139  Overall
#25  Document stores
#24  Key-value stores
#65  Relational DBMS
Websiterockset.comsplicemachine.comgithub.com/­STSSoft/­STSdb4www.tarantool.io
Technical documentationdocs.rockset.comsplicemachine.com/­how-it-workswww.tarantool.io/­en/­doc
DeveloperRocksetSplice MachineSTS Soft SCVK
Initial release2019201420112008
Current release3.1, March 20214.0.8, September 20152.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, commercial license availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#C and C++
Server operating systemshostedLinux
OS X
Solaris
Windows
WindowsBSD
Linux
macOS
Data schemeschema-freeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or datedynamic typingyesyes infoprimitive types and user defined types (classes)string, double, decimal, uuid, integer, blob, boolean, datetime
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.no infoingestion from XML files supportedno
Secondary indexesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLRead-only SQL queries, including JOINsyesnoFull-featured ANSI SQL support
APIs and other access methodsHTTP RESTJDBC
Native Spark Datasource
ODBC
.NET Client APIOpen binary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
Java
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoyes infoJavanoLua, C and SQL stored procedures
Triggersnoyesnoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users and organizations can be defined via Rockset consoleAccess rights for users, groups and roles according to SQL-standardnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
RocksetSplice MachineSTSdbTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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