DBMS > atoti vs. HEAVY.AI vs. Postgres-XL vs. SAP SQL Anywhere

System Properties Comparison atoti vs. HEAVY.AI vs. Postgres-XL vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Object oriented DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.61
Rank	#243	Overall
	#11	Object oriented DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

atoti.io

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

www.postgres-xl.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.atoti.io

docs.heavy.ai

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

ActiveViam

HEAVY.AI, Inc.

SAP

formerly Sybase

Initial release

2016

2014

since 2012, originally named StormDB

1992

Current release

5.10, January 2022

10 R1, October 2018

17, July 2015

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; enterprise edition available

Open Source

Mozilla public license

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

Java

C++ and CUDA

Server operating systems

Linux

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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.

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC
Thrift
Vega

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Python

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Round robin

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Database mirroring

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

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More resources

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