DBMS > Apache Impala vs. Apache Pinot vs. Linter vs. SiteWhere

System Properties Comparison Apache Impala vs. Apache Pinot vs. Linter vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

RDBMS for high security requirements

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

impala.apache.org

pinot.apache.org

linter.ru

github.com/sitewhere/sitewhere

Technical documentation

impala.apache.org/impala-docs.html

docs.pinot.apache.org

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation and contributors

relex.ru

SiteWhere

Initial release

2013

2015

1990

2010

Current release

4.1.0, June 2022

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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

C++

Java

C and C++

Java

Server operating systems

Linux

All OS with a Java JDK11 or higher

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

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC

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

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
Python

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

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

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

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