DBMS > Newts vs. OrientDB vs. TimesTen vs. Vitess vs. VoltDB

System Properties Comparison Newts vs. OrientDB vs. TimesTen vs. Vitess vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS based on Cassandra

Multi-model DBMS (Document, Graph, Key/Value)

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

opennms.github.io/newts

orientdb.org

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

vitess.io

www.voltdb.com

Technical documentation

github.com/OpenNMS/newts/wiki

www.orientdb.com/docs/last/index.html

docs.oracle.com/database/timesten-18.1

vitess.io/docs

docs.voltdb.com

Developer

OpenNMS Group

OrientDB LTD; CallidusCloud; SAP

Oracle, TimesTen Performance Software, HP

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

The Linux Foundation, PlanetScale

VoltDB Inc.

Initial release

2014

2010

1998

2013

2010

Current release

3.2.29, March 2024

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0, commercial licenses available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

Linux
OS X
Windows

All OS with a Java JDK (>= JDK 6)

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

Docker
Linux
macOS

Linux
OS X

for development

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

SQL-like query language, no joins

yes

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

HTTP REST
Java API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Java
PL/SQL

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java, Javascript

PL/SQL

yes

proprietary syntax

Java

Triggers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

not for MyISAM storage engine

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

ACID at shard level

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Users and roles with access to stored procedures

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