DBMS > EJDB vs. GridGain vs. TimesTen vs. Trafodion

System Properties Comparison EJDB vs. GridGain vs. TimesTen vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

GridGain is an in-memory computing platform, built on Apache Ignite

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

github.com/Softmotions/ejdb

www.gridgain.com

www.oracle.com/database/technologies/related/timesten.html

trafodion.apache.org

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

www.gridgain.com/docs/index.html

docs.oracle.com/en/database/other-databases/timesten/index.html

trafodion.apache.org/documentation.html

Developer

Softmotions

GridGain Systems, Inc.

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Apache Software Foundation, originally developed by HP

Initial release

2012

2007

1998

2014

Current release

GridGain 8.5.1

Release 22.1

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GPLv2

commercial, open source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net, Python, REST, SQL

C++, Java

Server operating systems

server-less

Linux
OS X
Solaris
Windows
z/OS

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

in-process shared library

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

ADO.NET
JDBC
ODBC

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Java
Node.js
PL/SQL
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

PL/SQL

Java Stored Procedures

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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