DBMS > GeoMesa vs. JaguarDB vs. Spark SQL vs. Teradata Aster vs. Transbase

System Properties Comparison GeoMesa vs. JaguarDB vs. Spark SQL vs. Teradata Aster vs. Transbase

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Performant, highly scalable DBMS for AI and IoT applications

Spark SQL is a component on top of 'Spark Core' for structured data processing

Platform for big data analytics on multistructured data sources and types

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Spatial DBMS

Key-value store
Vector DBMS

Relational DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.geomesa.org

www.jaguardb.com

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

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

www.jaguardb.com/support.html

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

CCRi and others

DataJaguar, Inc.

Apache Software Foundation

Teradata

Transaction Software GmbH

Initial release

2014

2015

2014

2005

1987

Current release

5.0.0, May 2024

3.3 July 2023

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GPL V3.0

Open Source

Apache 2.0

commercial

free development license

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++

the server part. Clients available in other languages

Scala

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

Java
Python
R
Scala

C
C#
C++
Java
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

R packages

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

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

User concepts

Access control

yes

depending on the DBMS used for storage

rights management via user accounts

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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