DBMS > AllegroGraph vs. ClickHouse vs. GridDB vs. searchxml vs. TimescaleDB

System Properties Comparison AllegroGraph vs. ClickHouse vs. GridDB vs. searchxml vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Scalable in-memory time series database optimized for IoT and Big Data

DBMS for structured and unstructured content wrapped with an application server

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Time Series DBMS

Native XML DBMS
Search engine

Time Series DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

allegrograph.com

clickhouse.com

griddb.net

www.searchxml.net/category/products

www.timescale.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

clickhouse.com/docs

docs.griddb.net

www.searchxml.net/support/handouts

docs.timescale.com

Developer

Franz Inc.

Clickhouse Inc.

Toshiba Corporation

informationpartners gmbh

Timescale

Initial release

2004

2016

2013

2015

2017

Current release

8.0, December 2023

v24.4.1.2088-stable, May 2024

5.1, August 2022

1.0

2.15.0, May 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Open Source

Apache 2.0

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

Linux

Windows

Linux
OS X
Windows

Data scheme

yes

RDF schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

bulk load of XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

Close to ANSI SQL (SQL/JSON + extensions)

SQL92, SQL-like TQL (Toshiba Query Language)

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API
SPARQL

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API
WebDAV
XQuery
XSLT

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

C++

most other programming languages supported via APIs

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

on the application server

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

key based and custom

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

yes

sychronisation to multiple collections

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Access rights for users can be defined per database

Domain, group and role-based access control at the document level and for application services

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

News

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.