DBMS > AlaSQL vs. HEAVY.AI vs. OpenTSDB vs. Postgres-XL vs. STSdb

System Properties Comparison AlaSQL vs. HEAVY.AI vs. OpenTSDB vs. Postgres-XL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Scalable Time Series DBMS based on HBase

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial 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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

alasql.org

github.com/heavyai/heavydb
www.heavy.ai

opentsdb.net

www.postgres-xl.org

github.com/STSSoft/STSdb4

Technical documentation

github.com/AlaSQL/alasql

docs.heavy.ai

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

www.postgres-xl.org/documentation

Developer

Andrey Gershun & Mathias R. Wulff

HEAVY.AI, Inc.

currently maintained by Yahoo and other contributors

STS Soft SC

Initial release

2014

2016

2011

2014

since 2012, originally named StormDB

2011

Current release

5.10, January 2022

10 R1, October 2018

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2; enterprise edition available

Open Source

LGPL

Open Source

Mozilla public license

Open Source

GPLv2, commercial license available

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++ and CUDA

Java

Server operating systems

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

Linux

Linux
Windows

Linux
macOS

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes

primitive types and user defined types (classes)

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

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

yes

distributed, parallel query execution

APIs and other access methods

JavaScript API

JDBC
ODBC
Thrift
Vega

HTTP API
Telnet API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC/Thrift
Python

Erlang
Go
Java
Python
R
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

based on HBase

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

selectable replication factor

based on HBase

none

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

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

MVCC

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

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More resources

DB-Engines blog posts

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4 July 2016, Matthias Gelbmann

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