DBMS > Apache Druid vs. Graph Engine vs. Linter vs. TempoIQ vs. TerminusDB

System Properties Comparison Apache Druid vs. Graph Engine vs. Linter vs. TempoIQ vs. TerminusDB

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

RDBMS for high security requirements

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS
Time Series DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

druid.apache.org

www.graphengine.io

linter.ru

tempoiq.com (offline)

terminusdb.com

Technical documentation

druid.apache.org/docs/latest/design

www.graphengine.io/docs/manual

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation and contributors

Microsoft

relex.ru

TempoIQ

DataChemist Ltd.

Initial release

2012

2010

1990

2012

2018

Current release

29.0.1, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

.NET and C

C and C++

Prolog, Rust

Server operating systems

Linux
OS X
Unix

.NET

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Data scheme

yes

schema-less columns are supported

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

SQL for querying

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
F#
Visual Basic

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C#
Java
JavaScript

Node.js
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

simple authentication-based access control

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

Imply advances Apache Druid real-time analytics database
20 September 2022, TechTarget

provided by Google News

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

[MCR2030-CAMS-ARISE-UNDRR Webinar] Preventing cascading failures of critical assets: Using the Open-Source ...
12 April 2022, United Nations Office for Disaster Risk Reduction

Irish start-ups received €28m from Enterprise Ireland in 2021
7 April 2022, SiliconRepublic.com

Disability tech innovator Avail Support acquired by US software firm
15 March 2021, The Irish Times

provided by Google News

Share this page