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

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

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonEsgynDB  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  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.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Enterprise-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 processingA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelObject oriented DBMSRelational DBMSDocument store
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteatoti.iowww.esgyn.cnspark.apache.org/­sqlwww.timescale.com
Technical documentationdocs.atoti.iospark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperActiveViamEsgynFatCloudApache Software FoundationTimescale
Initial release2015201220142017
Current release3.5.0 ( 2.13), September 20232.13.0, November 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaC#ScalaC
Server operating systemsLinuxWindowsLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.nonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes 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
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
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresPythonJava Stored Proceduresyes infovia applicationsnouser 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
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes, utilizing Spark Coreyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factornoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standard

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More resources
atotiEsgynDBFatDBSpark SQLTimescaleDB
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