DBMS > GeoMesa vs. Graph Engine vs. Postgres-XL vs. TempoIQ

System Properties Comparison GeoMesa vs. Graph Engine vs. Postgres-XL vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Spatial DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.geomesa.org

www.graphengine.io

www.postgres-xl.org

tempoiq.com (offline)

Technical documentation

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

www.graphengine.io/docs/manual

www.postgres-xl.org/documentation

Developer

CCRi and others

Microsoft

TempoIQ

Initial release

2014

2010

2014

since 2012, originally named StormDB

2012

Current release

4.0.5, February 2024

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT License

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

.NET and C

Server operating systems

.NET

Linux
macOS

Data scheme

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

simple authentication-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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