DBMS > GeoSpock vs. Oracle vs. PostGIS vs. TimescaleDB vs. XTDB

System Properties Comparison GeoSpock vs. Oracle vs. PostGIS vs. TimescaleDB 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

Widely used RDBMS

Spatial extension of PostgreSQL

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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

Primary database model

Secondary database models

Time Series DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

geospock.com

www.oracle.com/database

postgis.net

www.timescale.com

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

Technical documentation

docs.oracle.com/en/database

postgis.net/documentation

docs.timescale.com

www.xtdb.com/docs

Developer

GeoSpock

Oracle

Timescale

Juxt Ltd.

Initial release

1980

2005

2017

2019

Current release

2.0, September 2019

23c, September 2023

3.4.2, February 2024

2.13.0, November 2023

1.19, September 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL v2.0

Open Source

Apache 2.0

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

C and C++

Clojure

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

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

Data scheme

yes

Schemaless in JSON and XML columns

yes

schema-free

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

with proprietary extensions

yes

full PostgreSQL SQL syntax

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding, horizontal partitioning

yes

based on PostgreSQL

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

based on PostgreSQL

Source-replica replication with hot standby and reads on replicas

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

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

fine grained access rights according to SQL-standard

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