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. Spark SQL vs. Transbase

System Properties Comparison EsgynDB vs. Spark SQL vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#268  Overall
#123  Relational DBMS
Score20.56
Rank#34  Overall
#20  Relational DBMS
Score0.28
Rank#273  Overall
#126  Relational DBMS
Websitewww.esgyn.cnspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperEsgynApache Software FoundationTransaction Software GmbH
Initial release201520141987
Current release3.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaScalaC and C++
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine 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
EsgynDBSpark SQLTransbase
Recent citations in the news

Mphasis partners with Esgyn Corporation to provide specialized solutions to clients looking to harness big...
28 May 2019, Moneycontrol

Esgyn Corporation and Ampool Partner to Bring In-Memory Optimized Operational, Transactional and Real-Time Analytics to Hadoop.
18 May 2017, PR Newswire

The Apache Software Foundation Announces Apache® Trafodion™
10 January 2018, GlobeNewswire

provided by Google News

Beginner's Guide To Machine Learning With Apache Spark
16 July 2021, Analytics India Magazine

Latest big data developments in the realm of data lakehouse
23 July 2021, VentureBeat

Microsoft : Accelerate big data analytics with Spark 3.0 connector for SQL Server—now generally available
13 July 2021, marketscreener.com

Inside LinkedIn's Big Data Pipelines
1 August 2021, Analytics India Magazine

Start artificial intelligence for IoT in bite-size pieces
15 July 2021, TechTarget

provided by Google News

Job opportunities

Manager, Solution Architecture - Project Omnia
Deloitte, Phoenix, AZ

Data Warehouse Architect
J.Crew, New York, NY

SOFTWARE DEVELOPERS (327)
IdolSoft, Irving, TX

Data Scientist
Cloudflare, Austin, TX

Data Engineer
U-Haul, Phoenix, AZ

Senior Engineer - Hadoop/Spark
Amex, Phoenix, AZ

jobs by Indeed



Share this page

Featured Products

MariaDB logo

SkySQL, the ultimate
MariaDB cloud, is here.

Get started with SkySQL today!

Couchbase logo

SQL + JSON + NoSQL.
Power, flexibility & scale.
All open source.
Get started now.

Neo4j logo

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

Datastax Astra logo

Build cloud-native apps fast with Astra, the open-source, multi-cloud stack for
modern data apps.
Get started with 5 GB free..

Vertica logo

The fastest unified analytical warehouse at extreme scale with in-database machine learning. Try Vertica for free with no time limit.

Present your product here