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DBMS > Datomic vs. Faircom EDGE vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Datomic vs. Faircom EDGE vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  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 environmentsA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value store
Relational DBMS
Graph DBMSSearch engineSearch engine
Secondary database modelsVector 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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.datomic.comwww.faircom.com/­products/­faircom-edgegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperCognitectFairCom CorporationBaiduMicrosoftSphinx Technologies Inc.
Initial release20121979201820152001
Current release1.0.6735, June 2023V3, October 20200.9V13.5.1, February 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureANSI C, C++JavaC++
Server operating systemsAll OS with a Java VMAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
macOS
Unix
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyesno
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.noyesnono
Secondary indexesyesyesyes infoalso supports composite index and range indexyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes infoANSI SQL queriesnonoSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocol
Supported programming languagesClojure
Java
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Groovy
Java
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++asynchronous Gremlin script jobsnono
TriggersBy using transaction functionsyesnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning infoCustomizable business rules for partitioningyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
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 logsyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonovia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 developmentyesyesno
User concepts infoAccess controlnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Users, roles and permissionsyes infousing Azure authenticationno

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More resources
DatomicFaircom EDGE infoformerly c-treeEDGEHugeGraphMicrosoft Azure AI SearchSphinx
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