DBMS > Badger vs. ClickHouse vs. GeoMesa vs. Oracle Rdb

System Properties Comparison Badger vs. ClickHouse vs. GeoMesa vs. Oracle Rdb

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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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Website

github.com/dgraph-io/badger

clickhouse.com

www.geomesa.org

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

Technical documentation

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

clickhouse.com/docs

www.geomesa.org/documentation/stable/user/index.html

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

DGraph Labs

Clickhouse Inc.

CCRi and others

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2017

2016

2014

1984

Current release

v24.6.2.17-stable, July 2024

5.0.1, July 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache License 2.0

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

Implementation language

C++

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS

HP Open VMS

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

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

APIs and other access methods

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

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

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

key based and custom

depending on storage layer

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes, on a single node

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

depending on storage layer

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.

yes

depending on the DBMS used for storage

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