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DBMS > BigObject vs. Datomic vs. Sphinx vs. Splice Machine

System Properties Comparison BigObject vs. Datomic vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatomic  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen 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 Spark
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitebigobject.iowww.datomic.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.bigobject.iodocs.datomic.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperBigObject, Inc.CognitectSphinx Technologies Inc.Splice Machine
Initial release2015201220012014
Current release1.0.6735, June 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial infolimited edition freeOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Java
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nono
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language (SphinxQL)yes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
RESTful HTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuayes infoTransaction Functionsnoyes infoJava
TriggersnoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles according to SQL-standard

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More resources
BigObjectDatomicSphinxSplice Machine
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