DBMS > Hive vs. TempoIQ vs. ToroDB vs. Yaacomo

System Properties Comparison Hive vs. TempoIQ vs. ToroDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

hive.apache.org

tempoiq.com (offline)

github.com/torodb/server

yaacomo.com

Technical documentation

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

Developer

Apache Software Foundation

initially developed by Facebook

TempoIQ

8Kdata

Q2WEB GmbH

Initial release

2012

2016

2009

Current release

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL-V3

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

Server operating systems

All OS with a Java VM

All OS with a Java 7 VM

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

HTTP API

JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Eventual Consistency

Eventual Consistency
Immediate 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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

simple authentication-based access control

Access rights for users 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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