DBMS > JaguarDB vs. Newts vs. RocksDB vs. TimesTen

System Properties Comparison JaguarDB vs. Newts vs. RocksDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Time Series DBMS based on Cassandra

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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.

Primary database model

Key-value store
Vector DBMS

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.jaguardb.com

opennms.github.io/newts

rocksdb.org

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

Technical documentation

www.jaguardb.com/support.html

github.com/OpenNMS/newts/wiki

github.com/facebook/rocksdb/wiki

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

Developer

DataJaguar, Inc.

OpenNMS Group

Facebook, Inc.

Oracle

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

Initial release

2015

2014

2013

1998

Current release

3.3 July 2023

9.4.0, June 2024

Release 22.1

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

Apache 2.0

Open Source

BSD

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

C++

the server part. Clients available in other languages

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

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

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

HTTP REST
Java API

C++ API
Java API

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

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

rights management via user accounts

fine grained access rights according to SQL-standard

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