DBMS > Badger vs. ClickHouse vs. Datomic vs. Microsoft Access vs. TimesTen

System Properties Comparison Badger vs. ClickHouse vs. Datomic vs. Microsoft Access vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

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.)

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/dgraph-io/badger

clickhouse.com

www.datomic.com

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

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

godoc.org/github.com/dgraph-io/badger

clickhouse.com/docs

docs.datomic.com

developer.microsoft.com/en-us/access

docs.oracle.com/database/timesten-18.1

Developer

DGraph Labs

Clickhouse Inc.

Cognitect

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

2016

2012

1992

1998

Current release

v24.4.1.2088-stable, May 2024

1.0.6735, June 2023

1902 (16.0.11328.20222), March 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

limited edition free

commercial

Bundled with Microsoft Office

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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DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Java, Clojure

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

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

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

since Access 2010 using the ACE-engine

PL/SQL

Triggers

By using transaction functions

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

But extensive use of caching in the application peers

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

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

but no files for transaction logging

yes

by means of logfiles and checkpoints

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.

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

fine grained access rights according to SQL-standard

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