DBMS > GeoSpock vs. HBase vs. Oracle vs. Oracle Coherence vs. Spark SQL

System Properties Comparison GeoSpock vs. HBase vs. Oracle vs. Oracle Coherence vs. Spark SQL

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

Widely used RDBMS

Oracles in-memory data grid solution

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

geospock.com

hbase.apache.org

www.oracle.com/database

www.oracle.com/java/coherence

spark.apache.org/sql

Technical documentation

hbase.apache.org/book.html

docs.oracle.com/en/database

docs.oracle.com/en/middleware/standalone/coherence

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

GeoSpock

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Oracle

Apache Software Foundation

Initial release

2008

1980

2007

2014

Current release

2.0, September 2019

2.3.4, January 2021

23c, September 2023

14.1, August 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

Java

C and C++

Java

Scala

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

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

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Schemaless in JSON and XML columns

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Secondary indexes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

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++
Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

PL/SQL

also stored procedures in Java possible

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Sharding, horizontal partitioning

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

isolation level can be parameterized

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

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'

yes

User concepts

Access control

Access rights for users can be defined per table

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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