DBMS > GeoMesa vs. HEAVY.AI vs. VoltDB

System Properties Comparison GeoMesa vs. HEAVY.AI vs. VoltDB

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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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Spatial DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

www.geomesa.org

github.com/heavyai/heavydb
www.heavy.ai

www.voltdb.com

Technical documentation

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

docs.heavy.ai

docs.voltdb.com

Developer

CCRi and others

HEAVY.AI, Inc.

VoltDB Inc.

Initial release

2014

2016

2010

Current release

4.0.5, February 2024

5.10, January 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++ and CUDA

Java, C++

Server operating systems

Linux

Linux
OS X

for development

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
Thrift
Vega

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Multi-source replication

Multi-source 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

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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