DBMS > Dolt vs. GeoSpock vs. Google BigQuery vs. Oracle Coherence

System Properties Comparison Dolt vs. GeoSpock vs. Google BigQuery vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

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

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Spatial and temporal data processing engine for extreme data scale

Large scale data warehouse service with append-only tables

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store

Time Series DBMS

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

github.com/dolthub/dolt
www.dolthub.com

geospock.com

cloud.google.com/bigquery

www.oracle.com/java/coherence

Technical documentation

docs.dolthub.com

cloud.google.com/bigquery/docs

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

Developer

DoltHub Inc

GeoSpock

Google

Oracle

Initial release

2018

2010

2007

Current release

2.0, September 2019

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Server operating systems

Linux
macOS
Windows

hosted

All OS with a Java VM

Data scheme

yes

schema-free

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

temporal, categorical

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

CLI Client
HTTP REST

JDBC

RESTful HTTP/JSON API

JCache
JPA
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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

in JavaScript

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

yes

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

Access rights for users can be defined per table

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

authentification to access the cache via certificates or http basic authentication

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