DBMS > Apache Drill vs. Newts vs. OrientDB vs. TimesTen vs. VoltDB

System Properties Comparison Apache Drill vs. Newts vs. OrientDB vs. TimesTen vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Time Series DBMS based on Cassandra

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

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.

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

Document store
Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

drill.apache.org

opennms.github.io/newts

orientdb.org

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

www.voltdb.com

Technical documentation

drill.apache.org/docs

github.com/OpenNMS/newts/wiki

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

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

docs.voltdb.com

Developer

Apache Software Foundation

OpenNMS Group

OrientDB LTD; CallidusCloud; SAP

Oracle

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

VoltDB Inc.

Initial release

2012

2014

2010

1998

2010

Current release

1.20.3, January 2023

3.2.29, March 2024

Release 22.1

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache version 2

commercial

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)

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

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 SELECT statement is SQL:2003 compliant

SQL-like query language, no joins

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST
Java API

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

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++

Java

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

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java, Javascript

PL/SQL

Java

Triggers

Hooks

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

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

Depending on the underlying data source

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.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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