DBMS > EJDB vs. FatDB vs. Newts vs. Splice Machine vs. TimesTen

System Properties Comparison EJDB vs. FatDB vs. Newts vs. Splice Machine vs. TimesTen

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Time Series DBMS based on Cassandra

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Document store
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/Softmotions/ejdb

opennms.github.io/newts

splicemachine.com

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

Technical documentation

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

github.com/OpenNMS/newts/wiki

splicemachine.com/how-it-works

docs.oracle.com/database/timesten-18.1

Developer

Softmotions

FatCloud

OpenNMS Group

Splice Machine

Oracle, TimesTen Performance Software, HP

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

Initial release

2012

2014

1998

Current release

3.1, March 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

server-less

Windows

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

APIs and other access methods

in-process shared library

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP REST
Java API

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

via applications

yes

Java

PL/SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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