DBMS > AlaSQL vs. Infobright vs. SiriDB vs. Tkrzw vs. Transwarp Hippo

System Properties Comparison AlaSQL vs. Infobright vs. SiriDB vs. Tkrzw vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

alasql.org

ignitetech.com/softwarelibrary/infobrightdb

siridb.com

dbmx.net/tkrzw

www.transwarp.cn/en/subproduct/hippo

Technical documentation

github.com/AlaSQL/alasql

docs.siridb.com

Developer

Andrey Gershun & Mathias R. Wulff

Ignite Technologies Inc.; formerly InfoBright Inc.

Cesbit

Mikio Hirabayashi

Initial release

2014

2005

2017

2020

2023

Current release

0.9.3, August 2020

1.0, May 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

MIT License

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

C++

Server operating systems

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

Linux
Windows

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

Vector, Numeric and String

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

Knowledge Grid Technology used instead

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

ADO.NET
JDBC
ODBC

HTTP API

RESTful HTTP API

Supported programming languages

JavaScript

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++
Java
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

simple rights management via user accounts

Role based access control and fine grained access rights

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