DBMS > ClickHouse vs. Datomic vs. Dgraph vs. Riak KV vs. SAP SQL Anywhere

System Properties Comparison ClickHouse vs. Datomic vs. Dgraph vs. Riak KV vs. SAP SQL Anywhere

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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Distributed and scalable native Graph DBMS

Distributed, fault tolerant key-value store

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

clickhouse.com

www.datomic.com

dgraph.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

clickhouse.com/docs

docs.datomic.com

dgraph.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Clickhouse Inc.

Cognitect

Dgraph Labs, Inc.

OpenSource, formerly Basho Technologies

SAP

formerly Sybase

Initial release

2016

2012

2016

2009

1992

Current release

v24.4.1.2088-stable, May 2024

1.0.6735, June 2023

3.2.0, December 2022

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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.

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Implementation language

C++

Java, Clojure

Erlang

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

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

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP API
Native Erlang Interface

ADO.NET
HTTP API
JDBC
ODBC

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

Clojure
Java

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

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

Server-side scripts

Stored procedures

yes

Transaction Functions

Erlang

yes, in C/C++, Java, .Net or Perl

Triggers

By using transaction functions

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

But extensive use of caching in the application peers

yes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

But extensive use of caching in the application peers

Synchronous replication via Raft

selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between data sets can be stored

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

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.

Planned for future releases

yes, using Riak Security

fine grained access rights according to SQL-standard

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