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DBMS > JanusGraph vs. Microsoft Access vs. Spark SQL vs. Sphinx vs. TDSQL for MySQL

System Properties Comparison JanusGraph vs. Microsoft Access vs. Spark SQL vs. Sphinx vs. TDSQL for MySQL

Editorial information provided by DB-Engines
NameJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Spark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelGraph DBMSRelational DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitejanusgraph.orgwww.microsoft.com/­en-us/­microsoft-365/­accessspark.apache.org/­sqlsphinxsearch.comwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.janusgraph.orgdeveloper.microsoft.com/­en-us/­accessspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperLinux Foundation; originally developed as Titan by AureliusMicrosoftApache Software FoundationSphinx Technologies Inc.Tencent
Initial release20171992201420012013
Current release0.6.3, February 20231902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ScalaC++
Server operating systemsLinux
OS X
Unix
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hosted
Data schemeyesyesyesyesyes
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.nonono
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
DAO
ODBC
OLE DB
JDBC
ODBC
Proprietary protocolJDBC
ODBC
Supported programming languagesClojure
Java
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infosince Access 2010 using the ACE-enginenonoyes
Triggersyesyes infosince Access 2010 using the ACE-enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)noneyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Faunus, a graph analytics enginenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infobut no files for transaction loggingnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes infobut no files for transaction loggingyesyes 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.nono
User concepts infoAccess controlUser authentification and security via Rexster Graph Serverno infoa simple user-level security was built in till version Access 2003nonoUsers with fine-grained authorization concept

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More resources
JanusGraph infosuccessor of TitanMicrosoft AccessSpark SQLSphinxTDSQL for MySQL
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