DBMS > GridGain vs. OrigoDB vs. SpatiaLite vs. Teradata

System Properties Comparison GridGain vs. OrigoDB vs. SpatiaLite vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Spatial extension of SQLite

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Key-value store
Relational DBMS

Document store
Object oriented DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

www.gridgain.com

origodb.com

www.gaia-gis.it/fossil/libspatialite/index

www.teradata.com

Technical documentation

www.gridgain.com/docs/index.html

origodb.com/docs

www.gaia-gis.it/gaia-sins/spatialite_topics.html

docs.teradata.com

Developer

GridGain Systems, Inc.

Robert Friberg et al

Alessandro Furieri

Teradata

Initial release

2007

2009

under the name LiveDB

2008

1984

Current release

GridGain 8.5.1

5.0.0, August 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

server-less

hosted
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

yes

Secondary indexes

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

SQL 2016 + extensions

APIs and other access methods

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

.NET Client API
HTTP API
LINQ

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

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net

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

UDFs, stored procedures, table functions in parallel

Triggers

yes (cache interceptors and events)

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

Write ahead log

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

Role based authorization

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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