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DBMS > GigaSpaces vs. Graph Engine vs. RavenDB vs. Sphinx vs. Splice Machine

System Properties Comparison GigaSpaces vs. Graph Engine vs. RavenDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen 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 modelDocument store
Object oriented DBMS infoValues are user defined objects
Graph DBMS
Key-value store
Document storeSearch engineRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.gigaspaces.comwww.graphengine.ioravendb.netsphinxsearch.comsplicemachine.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.graphengine.io/­docs/­manualravendb.net/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGigaspaces TechnologiesMicrosoftHibernating RhinosSphinx Technologies Inc.Splice Machine
Initial release20002010201020012014
Current release15.5, September 20205.4, July 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMIT LicenseOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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 languageJava, C++, .Net.NET and CC#C++Java
Server operating systemsLinux
macOS
Solaris
Windows
.NETLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-99 for query and DML statementsnoSQL-like query language (RQL)SQL-like query language (SphinxQL)yes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C++
Java
Python
Scala
C#
C++
F#
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 proceduresyesyesyesnoyes infoJava
Triggersyes, event driven architecturenoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding 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 nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes 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.yesyesyes
User concepts infoAccess controlRole-based access controlAuthorization levels configured per client per databasenoAccess rights for users, groups and roles according to SQL-standard

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More resources
GigaSpacesGraph Engine infoformer name: TrinityRavenDBSphinxSplice Machine
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