DBMS > GridGain vs. SAP IQ vs. Snowflake vs. Stardog vs. Teradata

System Properties Comparison GridGain vs. SAP IQ vs. Snowflake vs. Stardog vs. Teradata

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Columnar RDBMS optimized for Big Data analytics

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Key-value store
Relational DBMS

column-oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	47.84
Rank	#21	Overall
	#15	Relational DBMS

Website

www.gridgain.com

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

www.snowflake.com

www.stardog.com

www.teradata.com

Technical documentation

www.gridgain.com/docs/index.html

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

docs.stardog.com

docs.teradata.com

Developer

GridGain Systems, Inc.

SAP, formerly Sybase

Snowflake Computing Inc.

Stardog-Union

Teradata

Initial release

2007

1994

2014

2010

1984

Current release

GridGain 8.5.1

16.1 SPS04, April 2019

7.3.0, May 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
macOS
Windows

hosted
Linux

Data scheme

yes

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

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

SQL 2016 + extensions

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

SAP/Sybase Replication Server

yes

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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