DBMS > OrigoDB vs. SpatiaLite vs. Splice Machine vs. Teradata

System Properties Comparison OrigoDB vs. SpatiaLite vs. Splice Machine vs. Teradata

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A fully ACID in-memory object graph database

Spatial extension of SQLite

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

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	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	47.84
Rank	#21	Overall
	#15	Relational DBMS

Website

origodb.com

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

splicemachine.com

www.teradata.com

Technical documentation

origodb.com/docs

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

splicemachine.com/how-it-works

docs.teradata.com

Developer

Robert Friberg et al

Alessandro Furieri

Splice Machine

Teradata

Initial release

2009

under the name LiveDB

2008

2014

1984

Current release

5.0.0, August 2020

3.1, March 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

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

Open Source

AGPL 3.0, commercial license available

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

C++

Java

Server operating systems

Linux
Windows

server-less

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

yes

Typing

predefined data types such as float or date

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.

can be achieved using .NET

yes

Secondary indexes

yes

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

.NET Client API
HTTP API
LINQ

JDBC
Native Spark Datasource
ODBC

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

Supported programming languages

.Net

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

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

Server-side scripts

Stored procedures

yes

Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

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

Role based authorization

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

fine grained access rights according to SQL-standard

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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

show all

Recent citations in the news

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

Splice Machine Hadoop RDBMS Integrated with RedPoint Solution to Deliver Big Data Digital Marketing Platform
7 April 2015, The Fast Mode

provided by Google News

Connecting Teradata Vantage to Amazon Athena | AWS Partner Network (APN) Blog
23 April 2024, AWS Blog

An interview with Teradata CFO Claire Bramley
9 February 2024, McKinsey

Teradata's stock tumbles on flat revenue and soft guidance
12 February 2024, SiliconANGLE News

Teradata Appoints Richard Petley as Chief Revenue Officer
5 April 2024, Business Wire

Louisiana State Employees Retirement System Purchases New Shares in Teradata Co. (NYSE:TDC)
23 April 2024, MarketBeat

provided by Google News

Share this page