DBMS > GeoMesa vs. Hypertable vs. Kinetica vs. Postgres-XL

System Properties Comparison GeoMesa vs. Hypertable vs. Kinetica vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully vectorized database across both GPUs and CPUs

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

Primary database model

Spatial DBMS

Wide column store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

www.geomesa.org

www.kinetica.com

www.postgres-xl.org

Technical documentation

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

docs.kinetica.com

www.postgres-xl.org/documentation

Developer

CCRi and others

Hypertable Inc.

Kinetica

Initial release

2014

2009

2012

2014

since 2012, originally named StormDB

Current release

5.0.0, May 2024

0.9.8.11, March 2016

7.1, August 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Mozilla public 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++

C, C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Linux
macOS

Data scheme

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

C++ API
Thrift

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

selectable replication factor on file system level

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

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

MVCC

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

GPU vRAM or System RAM

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles on table level

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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