DBMS > Amazon Redshift vs. Hive vs. OpenTSDB vs. XTDB

System Properties Comparison Amazon Redshift vs. Hive vs. OpenTSDB vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Scalable Time Series DBMS based on HBase

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Time Series DBMS

Document store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/redshift

hive.apache.org

opentsdb.net

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/redshift

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

opentsdb.net/docs/build/html/index.html

www.xtdb.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

initially developed by Facebook

currently maintained by Yahoo and other contributors

Juxt Ltd.

Initial release

2012

2011

2019

Current release

3.1.3, April 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

LGPL

Open Source

MIT 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

Clojure

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes, extensible-data-notation format

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift

HTTP API
Telnet API

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
PHP
Python

Erlang
Go
Java
Python
R
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

yes, each node contains all data

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

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.