DBMS > ClickHouse vs. EXASOL vs. Google Cloud Firestore vs. LMDB vs. TerarkDB

System Properties Comparison ClickHouse vs. EXASOL vs. Google Cloud Firestore vs. LMDB vs. TerarkDB

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.

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A high performant, light-weight, embedded key-value database library

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store

Key-value store

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	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

clickhouse.com

www.exasol.com

firebase.google.com/products/firestore

www.symas.com/symas-embedded-database-lmdb

github.com/bytedance/terarkdb

Technical documentation

clickhouse.com/docs

www.exasol.com/resources

firebase.google.com/docs/firestore

www.lmdb.tech/doc

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Clickhouse Inc.

Exasol

Google

Symas

ByteDance, originally Terark

Initial release

2016

2000

2017

2011

2016

Current release

v24.4.1.2088-stable, May 2024

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

Implementation language

C++

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux
Unix
Windows

Data scheme

yes

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

.Net
JDBC
ODBC
WebSocket

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

C++ API
Java API

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

Java
Lua
Python
R

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Using Cloud Dataflow

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

yes

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

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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