DBMS > AlaSQL vs. HBase vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

System Properties Comparison AlaSQL vs. HBase vs. RocksDB vs. Tkrzw vs. Transwarp KunDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Relational DBMS

Wide column store

Key-value store

Relational DBMS

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	30.50
Rank	#26	Overall
	#2	Wide column stores

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

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

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/AlaSQL/alasql

hbase.apache.org/book.html

github.com/facebook/rocksdb/wiki

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Facebook, Inc.

Mikio Hirabayashi

Transwarp

Initial release

2014

2008

2013

2020

Current release

2.3.4, January 2021

9.2.1, May 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache version 2

Open Source

BSD

Open Source

Apache Version 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.

Implementation language

JavaScript

Java

C++

Server operating systems

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

Linux
Unix
Windows

using Cygwin

Linux

Linux
macOS

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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

yes

APIs and other access methods

JavaScript API

Java API
RESTful HTTP API
Thrift

C++ API
Java API

Supported programming languages

JavaScript

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

none

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

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

Single row ACID (across millions of columns)

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

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

yes

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