DBMS > Apache Phoenix vs. Linter vs. OpenTSDB vs. XTDB

System Properties Comparison Apache Phoenix vs. Linter vs. OpenTSDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

RDBMS for high security requirements

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

Secondary database models

Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

phoenix.apache.org

linter.ru

opentsdb.net

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

Technical documentation

phoenix.apache.org

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

www.xtdb.com/docs

Developer

Apache Software Foundation

relex.ru

currently maintained by Yahoo and other contributors

Juxt Ltd.

Initial release

2014

1990

2011

2019

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

Open Source

MIT License

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

Clojure

Server operating systems

Linux
Unix
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Windows

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

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP API
Telnet API

HTTP REST
JDBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Erlang
Go
Java
Python
R
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

based on HBase

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or 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

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

provided by Google News

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

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