DBMS > chDB vs. PouchDB vs. SingleStore vs. SQLite vs. SQream DB

System Properties Comparison chDB vs. PouchDB vs. SingleStore vs. SQLite vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

An embedded SQL OLAP Engine powered by ClickHouse

JavaScript DBMS with an API inspired by CouchDB

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Widely used embeddable, in-process RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

github.com/chdb-io/chdb

Technical documentation

doc.chdb.io

pouchdb.com/guides

docs.singlestore.com

www.sqlite.org/docs.html

docs.sqream.com

Developer

Apache Software Foundation

SingleStore Inc.

Dwayne Richard Hipp

SQream Technologies

Initial release

2023

2012

2013

2000

2017

Current release

7.1.1, June 2019

8.5, January 2024

3.45.3 (15 April 2024), April 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

free developer edition available

Open Source

Public Domain

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

JavaScript

C++, Go

C++, CUDA, Haskell, Java, Scala

Server operating systems

server-less

server-less, requires a JavaScript environment (browser, Node.js)

Linux

64 bit version required

server-less

Linux

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes, ANSI Standard SQL Types

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

via views

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

but no triggers and foreign keys

yes

SQL-92 is not fully supported

yes

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net
JDBC
ODBC

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

JavaScript

Bash
C
C#
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

hash partitioning

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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