DBMS > Databend vs. H2 vs. Hive vs. TempoIQ

System Properties Comparison Databend vs. H2 vs. Hive vs. TempoIQ

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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.

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

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

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.h2database.com

hive.apache.org

tempoiq.com (offline)

Technical documentation

docs.databend.com

www.h2database.com/html/main.html

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

Developer

Databend Labs

Thomas Mueller

Apache Software Foundation

initially developed by Facebook

TempoIQ

Initial release

2021

2005

2012

Current release

1.0.59, April 2023

2.2.220, July 2023

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2

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

Rust

Java

Server operating systems

hosted
Linux
macOS

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
Thrift

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Java

C++
Java
PHP
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

user defined functions and integration of map-reduce

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

simple authentication-based access control

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More resources

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