DBMS > AlaSQL vs. Badger vs. HBase vs. KeyDB vs. RocksDB

System Properties Comparison AlaSQL vs. Badger vs. HBase vs. KeyDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Relational DBMS

Key-value store

Wide column store

Key-value store

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

alasql.org

github.com/dgraph-io/badger

hbase.apache.org

github.com/Snapchat/KeyDB
keydb.dev

rocksdb.org

Technical documentation

github.com/AlaSQL/alasql

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

hbase.apache.org/book.html

docs.keydb.dev

github.com/facebook/rocksdb/wiki

Developer

Andrey Gershun & Mathias R. Wulff

DGraph Labs

Apache Software Foundation

Apache top-level project, originally developed by Powerset

EQ Alpha Technology Ltd.

Facebook, Inc.

Initial release

2014

2017

2008

2019

2013

Current release

2.3.4, January 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

BSD-3

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java

C++

Server operating systems

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

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

partial

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

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

SQL

Support of SQL

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

APIs and other access methods

JavaScript API

Java API
RESTful HTTP API
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

C++ API
Java API

Supported programming languages

JavaScript

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

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

Single row ACID (across millions of columns)

Optimistic locking, atomic execution of commands blocks and scripts

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple password-based access control and ACL

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