DBMS > GeoMesa vs. Sadas Engine vs. Teradata vs. ToroDB

System Properties Comparison GeoMesa vs. Sadas Engine vs. Teradata vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A hybrid cloud data analytics software platform (Teradata Vantage)

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Spatial DBMS

Relational DBMS

Document store

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.geomesa.org

www.sadasengine.com

www.teradata.com

github.com/torodb/server

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.teradata.com

Developer

CCRi and others

SADAS s.r.l.

Teradata

8Kdata

Initial release

2014

2006

1984

2016

Current release

5.0.0, May 2024

8.0

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free trial version available

commercial

Open Source

AGPL-V3

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

Scala

C++

Java

Server operating systems

AIX
Linux
Windows

hosted
Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

Supported programming languages

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

Server-side scripts

Stored procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency
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.

depending on storage layer

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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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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