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

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

Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  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.
DescriptionOpen 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 GPU-based, columnar RDBMS for big data analytics workloadsA high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelSearch engineRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitesphinxsearch.comsplicemachine.comsqream.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperSphinx Technologies Inc.Splice MachineSQream TechnologiesAlex KashirinTeradata
Initial release20012014201720202005
Current release3.5.1, February 20233.1, March 20212022.1.6, December 20220.5, April 2021
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercialOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++, CUDA, Haskell, Java, ScalaC++
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
LinuxLinuxLinux
Data schemeyesyesyesschema-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 datenoyesyes, ANSI Standard SQL Typesyes
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.noyes infoin Aster File Store
Secondary indexesyes infofull-text index on all search fieldsyesnoyes
SQL infoSupport of SQLSQL-like query language (SphinxQL)yesyesSQL-like query languageyes
APIs and other access methodsProprietary protocolJDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C++C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infoJavauser defined functions in PythonnoR packages
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
noneyes 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 methodsnoYes, via Full Spark Integrationnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
SphinxSplice MachineSQream DBSWC-DB infoSuper Wide Column DatabaseTeradata Aster
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