DBMS > GeoSpock vs. Hive vs. KairosDB vs. Lovefield vs. ToroDB

System Properties Comparison GeoSpock vs. Hive vs. KairosDB vs. Lovefield vs. ToroDB

Editorial information provided by DB-Engines

Name

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

ToroDB seems to be discontinued. Therefore it is 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

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Time Series DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

geospock.com

hive.apache.org

github.com/kairosdb/kairosdb

google.github.io/lovefield

github.com/torodb/server

Technical documentation

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

kairosdb.github.io

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

Developer

GeoSpock

Apache Software Foundation

initially developed by Facebook

Google

8Kdata

Initial release

2012

2013

2014

2016

Current release

2.0, September 2019

3.1.3, April 2022

1.2.2, November 2018

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL-V3

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

Java

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C++
Java
PHP
Python

Java
JavaScript

Node.js
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

based on Cassandra

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

simple password-based access control

Access rights for users and roles

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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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