DBMS > GeoMesa vs. NSDb vs. Transbase

System Properties Comparison GeoMesa vs. NSDb vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

www.geomesa.org

nsdb.io

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

Technical documentation

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

nsdb.io/Architecture

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

Developer

CCRi and others

Transaction Software GmbH

Initial release

2014

2017

1987

Current release

4.0.5, February 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Java, Scala

C and C++

Server operating systems

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Scala

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

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