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DBMS > EsgynDB vs. FatDB vs. Spark SQL vs. Stardog vs. TimescaleDB

System Properties Comparison EsgynDB vs. FatDB vs. Spark SQL vs. Stardog vs. TimescaleDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparisonTimescaleDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSGraph DBMS
RDF store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.esgyn.cnspark.apache.org/­sqlwww.stardog.comwww.timescale.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.comdocs.timescale.com
DeveloperEsgynFatCloudApache Software FoundationStardog-UnionTimescale
Initial release20152012201420102017
Current release3.5.0 ( 2.13), September 20237.3.0, May 20202.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC#ScalaJavaC
Server operating systemsLinuxWindowsLinux
OS X
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 infoImport/export of XML data possibleyes
Secondary indexesyesyesnoyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresyes infovia applicationsnouser defined functions and aggregates, HTTP Server extensions in Javauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infovia applicationsnoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factornoneMulti-source replication in HA-ClusterSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsnoAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
EsgynDBFatDBSpark SQLStardogTimescaleDB
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