DBMS > ClickHouse vs. Graph Engine vs. Teradata vs. TerminusDB vs. VelocityDB

System Properties Comparison ClickHouse vs. Graph Engine vs. Teradata vs. TerminusDB vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

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.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

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

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

Technical documentation

clickhouse.com/docs

www.graphengine.io/docs/manual

docs.teradata.com

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Clickhouse Inc.

Microsoft

Teradata

DataChemist Ltd.

VelocityDB Inc

Initial release

2016

2010

1984

2018

2011

Current release

v24.4.1.2088-stable, May 2024

Teradata Vantage 1.0 MU2, January 2019

11.0.0, January 2023

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

commercial

Open Source

GPL V3

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.

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

.NET and C

Prolog, Rust

Server operating systems

FreeBSD
Linux
macOS

.NET

hosted
Linux

Linux

Any that supports .NET

Data scheme

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL 2016 + extensions

SQL-like query language (WOQL)

APIs and other access methods

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

RESTful HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

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++
F#
Visual Basic

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

JavaScript
Python

.Net

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning

Sharding

Hashing

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
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

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

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.

fine grained access rights according to SQL-standard

Role-based access control

Based on Windows Authentication

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