DBMS > EXASOL vs. HEAVY.AI vs. SAP IQ vs. SiriDB vs. Snowflake

System Properties Comparison EXASOL vs. HEAVY.AI vs. SAP IQ vs. SiriDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Columnar RDBMS optimized for Big Data analytics

Open Source Time Series DBMS

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

column-oriented

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

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

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

siridb.com

www.snowflake.com

Technical documentation

www.exasol.com/resources

docs.heavy.ai

help.sap.com/docs/SAP_IQ

docs.siridb.com

docs.snowflake.net/manuals/index.html

Developer

Exasol

HEAVY.AI, Inc.

SAP, formerly Sybase

Cesbit

Snowflake Computing Inc.

Initial release

2000

2016

1994

2017

2014

Current release

5.10, January 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

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

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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.