DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > EsgynDB vs. FatDB vs. Spark SQL vs. Teradata Aster vs. TimescaleDB

System Properties Comparison EsgynDB vs. FatDB vs. Spark SQL vs. Teradata Aster vs. TimescaleDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  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.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines 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 processingPlatform for big data analytics on multistructured data sources and typesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSRelational DBMSTime 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
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.esgyn.cnspark.apache.org/­sqlwww.timescale.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.timescale.com
DeveloperEsgynFatCloudApache Software FoundationTeradataTimescale
Initial release20152012201420052017
Current release3.5.0 ( 2.13), September 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen 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 languageC++, JavaC#ScalaC
Server operating systemsLinuxWindowsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
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.nonoyes infoin Aster File Storeyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyesyes 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
ODBC
OLE DB
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
C
C#
C++
Java
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresyes infovia applicationsnoR packagesuser 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 applicationsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factornoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
EsgynDBFatDBSpark SQLTeradata AsterTimescaleDB
Recent citations in the news

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here