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

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

Editorial information provided by DB-Engines
NameSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  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 fully ACID transactional, developer-friendly, multi-model DBMSA high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelSearch engineRelational DBMSDocument store
Graph DBMS
Wide 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
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitesphinxsearch.comsplicemachine.comsurrealdb.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationsphinxsearch.com/­docssplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperSphinx Technologies Inc.Splice MachineSurrealDB LtdAlex KashirinTeradata
Initial release20012014202220202005
Current release3.5.1, February 20233.1, March 2021v1.1.1, January 20240.5, April 2021
License infoCommercial or Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen SourceOpen 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++JavaRustC++
Server operating systemsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
LinuxLinux
Data schemeyesyesschema-freeschema-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 datenoyesyesyes
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 fieldsyesyes
SQL infoSupport of SQLSQL-like query language (SphinxQL)yesSQL-like query languageSQL-like query languageyes
APIs and other access methodsProprietary protocolJDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
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
Deno
Go
JavaScript (Node.js)
Rust
C++C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infoJavanoR packages
Triggersnoyesnono
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 PartitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-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 methodsnoYes, via Full Spark Integrationnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesno
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-standardyes, based on authentication and database rulesfine grained access rights according to SQL-standard

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More resources
SphinxSplice MachineSurrealDBSWC-DB infoSuper Wide Column DatabaseTeradata Aster
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