DBMS > AlaSQL vs. BigchainDB vs. H2 vs. KeyDB vs. RethinkDB

System Properties Comparison AlaSQL vs. BigchainDB vs. H2 vs. KeyDB vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

alasql.org

www.bigchaindb.com

www.h2database.com

github.com/Snapchat/KeyDB
keydb.dev

rethinkdb.com

Technical documentation

github.com/AlaSQL/alasql

bigchaindb.readthedocs.io/en/latest

www.h2database.com/html/main.html

docs.keydb.dev

rethinkdb.com/docs

Developer

Andrey Gershun & Mathias R. Wulff

Thomas Mueller

EQ Alpha Technology Ltd.

The Linux Foundation

since July 2017

Initial release

2014

2016

2005

2019

2009

Current release

2.2.220, July 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

AGPL v3

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD-3

Open Source

Apache Version 2

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.

Implementation language

JavaScript

Python

Java

C++

Server operating systems

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

Linux

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

string, binary, float, bool, date, geometry

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

by using the Redis Search module

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

APIs and other access methods

JavaScript API

CLI Client
RESTful HTTP API

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

JavaScript

Go
Haskell
Java
JavaScript
Python
Ruby

Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

Lua

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC based

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes,with MongoDB ord RethinkDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes

fine grained access rights according to SQL-standard

simple password-based access control and ACL

yes

users and table-level permissions

More information provided by the system vendor

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