DBMS > BigObject vs. GeoSpock vs. MySQL vs. Oracle NoSQL vs. SpaceTime

System Properties Comparison BigObject vs. GeoSpock vs. MySQL vs. Oracle NoSQL vs. SpaceTime

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for real-time computations and queries

Spatial and temporal data processing engine for extreme data scale

Widely used open source RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Spatial DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

bigobject.io

geospock.com

www.mysql.com

www.oracle.com/database/nosql/technologies/nosql

www.mireo.com/spacetime

Technical documentation

docs.bigobject.io

dev.mysql.com/doc

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

BigObject, Inc.

GeoSpock

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Mireo

Initial release

2015

1995

2011

2020

Current release

2.0, September 2019

8.4.0, April 2024

23.3, December 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, Javascript

C and C++

Java

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

yes

temporal, categorical

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for query only (using Presto)

yes

with proprietary extensions

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
C++
Python

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

table locks or row locks depending on storage engine

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.

yes

off heap cache

User concepts

Access control

Access rights for users can be defined per table

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

yes

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