DBMS > AlaSQL vs. EventStoreDB vs. Infobright vs. openGauss vs. OpenTSDB

System Properties Comparison AlaSQL vs. EventStoreDB vs. Infobright vs. openGauss vs. OpenTSDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Scalable Time Series DBMS based on HBase

Primary database model

Document store
Relational DBMS

Event Store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial 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	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

alasql.org

www.eventstore.com

ignitetech.com/softwarelibrary/infobrightdb

gitee.com/opengauss
opengauss.org

opentsdb.net

Technical documentation

github.com/AlaSQL/alasql

developers.eventstore.com

docs.opengauss.org/en
gitee.com/opengauss/docs

opentsdb.net/docs/build/html/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Event Store Limited

Ignite Technologies Inc.; formerly InfoBright Inc.

Huawei and openGauss community

currently maintained by Yahoo and other contributors

Initial release

2014

2012

2005

2019

2011

Current release

21.2, February 2021

3.0, March 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

commercial

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

Open Source

LGPL

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, C++, Java

Java

Server operating systems

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

Linux
Windows

Linux

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

ANSI SQL 2011

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP API
Telnet 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++
Java

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash)

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

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

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

provided by Google News

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

Share this page