DBMS > Hive vs. Transbase vs. Valentina Server vs. Warp 10

System Properties Comparison Hive vs. Transbase vs. Valentina Server vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

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

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

Object-relational database and reports server

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

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	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

hive.apache.org

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

www.valentina-db.net

www.warp10.io

Technical documentation

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

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

valentina-db.com/docs/dokuwiki/v5/doku.php

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

initially developed by Facebook

Transaction Software GmbH

Paradigma Software

SenX

Initial release

2012

1987

1999

2015

Current release

3.1.3, April 2022

Transbase 8.3, 2022

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free development license

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

C++
Java
PHP
Python

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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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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