DBMS > GeoSpock vs. Hawkular Metrics vs. HEAVY.AI vs. PostGIS vs. XTDB

System Properties Comparison GeoSpock vs. Hawkular Metrics vs. HEAVY.AI vs. PostGIS vs. XTDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Spatial extension of PostgreSQL

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Time Series DBMS

Spatial DBMS

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

geospock.com

www.hawkular.org

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

postgis.net

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.heavy.ai

postgis.net/documentation

www.xtdb.com/docs

Developer

GeoSpock

Community supported by Red Hat

HEAVY.AI, Inc.

Juxt Ltd.

Initial release

2014

2016

2005

2019

Current release

2.0, September 2019

5.10, January 2022

3.4.2, February 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL v2.0

Open Source

MIT License

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

Java, Javascript

Java

C++ and CUDA

Clojure

Server operating systems

hosted

Linux
OS X
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

HTTP REST

JDBC
ODBC
Thrift
Vega

HTTP REST
JDBC

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on Cassandra

Sharding

Round robin

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

yes

based on PostgreSQL

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

More information provided by the system vendor

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

Making the most of geospatial intelligence
14 April 2023, InfoWorld

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

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