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DBMS > Datomic vs. Faircom EDGE vs. Sphinx vs. Splice Machine

System Properties Comparison Datomic vs. Faircom EDGE vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsOpen 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 DBMSKey-value store
Relational DBMS
Search engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgesphinxsearch.comsplicemachine.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCognitectFairCom CorporationSphinx Technologies Inc.Splice Machine
Initial release2012197920012014
Current release1.0.6735, June 2023V3, October 20203.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen 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, ClojureANSI C, C++C++Java
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesnoyes
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
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoANSI SQL queriesSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
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 proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++noyes infoJava
TriggersBy using transaction functionsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningSharding 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 nodesnone infoBut extensive use of caching in the application peersyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneMulti-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 systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGESphinxSplice Machine
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