DBMS > Apache IoTDB vs. ClickHouse vs. EXASOL vs. TigerGraph vs. TypeDB

System Properties Comparison Apache IoTDB vs. ClickHouse vs. EXASOL vs. TigerGraph vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Time Series DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

clickhouse.com/docs

www.exasol.com/resources

docs.tigergraph.com

typedb.com/docs

Developer

Apache Software Foundation

Clickhouse Inc.

Exasol

Vaticle

Initial release

2018

2016

2000

2017

2016

Current release

1.1.0, April 2023

v24.4.1.2088-stable, May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL Version 3, commercial licenses available

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.
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.

Implementation language

Java

C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
macOS

Linux

Linux
OS X
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC
Native API

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

.Net
JDBC
ODBC
WebSocket

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C
C#
C++
Go
Java
Python
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

Java
Lua
Python
R

C++
Java

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

key based and custom

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

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

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Hadoop integration

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

substituted by the relationship feature

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

In-memory capabilities

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

yes

User concepts

Access control

yes

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, groups and roles according to SQL-standard

Role-based access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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