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DBMS > Amazon DocumentDB vs. EXASOL vs. GridGain vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. EXASOL vs. GridGain vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEXASOL  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.GridGain is an in-memory computing platform, built on Apache IgniteOpen 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 storeRelational DBMSKey-value store
Relational DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.exasol.comwww.gridgain.comsphinxsearch.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourceswww.exasol.com/­resourceswww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperExasolGridGain Systems, Inc.Sphinx Technologies Inc.Splice Machine
Initial release20192000200720012014
Current releaseGridGain 8.5.13.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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 languageJava, C++, .NetC++Java
Server operating systemshostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonoyes
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).Net
JDBC
ODBC
WebSocket
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Java
Lua
Python
R
C#
C++
Java
PHP
Python
Ruby
Scala
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 proceduresnouser defined functionsyes (compute grid and cache interceptors can be used instead)noyes infoJava
Triggersnoyesyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding 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-availability zones for high availability, asynchronous replication for up to 15 read replicasyes (replicated cache)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoHadoop integrationyes (compute grid and hadoop accelerator)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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 controlAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardSecurity Hooks for custom implementationsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBEXASOLGridGainSphinxSplice Machine
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