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DBMS > Rockset vs. Sphinx vs. Splice Machine vs. SWC-DB vs. Teradata Aster

System Properties Comparison Rockset vs. Sphinx vs. Splice Machine vs. SWC-DB vs. Teradata Aster

Editorial information provided by DB-Engines
NameRockset  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeSearch engineRelational DBMSWide column storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#211  Overall
#35  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiterockset.comsphinxsearch.comsplicemachine.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.rockset.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperRocksetSphinx Technologies Inc.Splice MachineAlex KashirinTeradata
Initial release20192001201420202005
Current release3.5.1, February 20233.1, March 20210.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++JavaC++
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
LinuxLinux
Data schemeschema-freeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or datedynamic typingnoyesyes
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 supportednoyes infoin Aster File Store
Secondary indexesall fields are automatically indexedyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLRead-only SQL queries, including JOINsSQL-like query language (SphinxQL)yesSQL-like query languageyes
APIs and other access methodsHTTP RESTProprietary protocolJDBC
Native Spark Datasource
ODBC
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyes infoJavanoR packages
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and organizations can be defined via Rockset consolenoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
RocksetSphinxSplice MachineSWC-DB infoSuper Wide Column DatabaseTeradata Aster
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