DBMS > HEAVY.AI vs. Percona Server for MySQL vs. Postgres-XL vs. STSdb

System Properties Comparison HEAVY.AI vs. Percona Server for MySQL vs. Postgres-XL vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

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

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

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

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	2.21
Rank	#121	Overall
	#58	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

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

www.percona.com/software/mysql-database/percona-server

www.postgres-xl.org

github.com/STSSoft/STSdb4

Technical documentation

docs.heavy.ai

www.percona.com/downloads/Percona-Server-LATEST

www.postgres-xl.org/documentation

Developer

HEAVY.AI, Inc.

Percona

STS Soft SC

Initial release

2016

2008

2014

since 2012, originally named StormDB

2011

Current release

5.10, January 2022

8.0.36-28, 2024

10 R1, October 2018

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2

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

C++ and CUDA

C and C++

Server operating systems

Linux

Linux
macOS

Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

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

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

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

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication
XtraDB Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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