DBMS > ClickHouse vs. Datomic vs. GridGain vs. Microsoft Access

System Properties Comparison ClickHouse vs. Datomic vs. GridGain vs. Microsoft Access

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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

GridGain is an in-memory computing platform, built on Apache Ignite

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Relational DBMS

Key-value store
Relational DBMS

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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

clickhouse.com

www.datomic.com

www.gridgain.com

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

clickhouse.com/docs

docs.datomic.com

www.gridgain.com/docs/index.html

developer.microsoft.com/en-us/access

Developer

Clickhouse Inc.

Cognitect

GridGain Systems, Inc.

Microsoft

Initial release

2016

2012

2007

1992

Current release

v24.4.1.2088-stable, May 2024

1.0.6735, June 2023

GridGain 8.5.1

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

limited edition free

commercial

Bundled with Microsoft Office

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

Java, C++, .Net

C++

Server operating systems

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

ANSI-99 for query and DML statements, subset of DDL

yes

but not compliant to any SQL standard

APIs and other access methods

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

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
DAO
ODBC
OLE DB

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++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Transaction Functions

yes (compute grid and cache interceptors can be used instead)

yes

since Access 2010 using the ACE-engine

Triggers

By using transaction functions

yes (cache interceptors and events)

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

But extensive use of caching in the application peers

Sharding

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

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

but no files for transaction logging

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

but no files for transaction logging

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.

Security Hooks for custom implementations

a simple user-level security was built in till version Access 2003

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