DBMS > GeoSpock vs. Hive vs. Lovefield vs. Transbase

System Properties Comparison GeoSpock vs. Hive vs. Lovefield vs. Transbase

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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

Spatial and temporal data processing engine for extreme data scale

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable relational database for web apps written in pure JavaScript

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

geospock.com

hive.apache.org

google.github.io/lovefield

www.transaction.de/en/products/transbase.html

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/lovefield/blob/master/docs/spec_index.md

www.transaction.de/en/products/transbase/features.html

Developer

GeoSpock

Apache Software Foundation

initially developed by Facebook

Google

Transaction Software GmbH

Initial release

2012

2014

1987

Current release

2.0, September 2019

3.1.3, April 2022

2.1.12, February 2017

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

free development 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

JavaScript

C and C++

Server operating systems

hosted

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
PHP
Python

JavaScript

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users can be defined per table

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Recent citations in the news

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

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

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

UK-based database GeoSpock bags $5.4m, to expand into
6 October 2020, Tech in Asia

provided by Google News

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