DBMS > Apache Impala vs. Infobright vs. Sadas Engine vs. StarRocks

System Properties Comparison Apache Impala vs. Infobright vs. Sadas Engine vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Relational DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

impala.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.sadasengine.com

www.starrocks.io

Technical documentation

impala.apache.org/impala-docs.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ignite Technologies Inc.; formerly InfoBright Inc.

SADAS s.r.l.

The Linux Foundation

since Feb 2023

Initial release

2013

2005

2006

2020

Current release

4.1.0, June 2022

8.0

3.3, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

free trial version available

Open Source

Apache Version 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

C++

C++, Java

Server operating systems

Linux

Linux
Windows

AIX
Linux
Windows

Linux

Data scheme

yes

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
MySQL protocol

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

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.

yes

managed by 'Learn by Usage'

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

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

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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

CelerData: How This Company Reduces Data Migration And Direct Analysis Costs In Data Lakes
21 December 2023, Pulse 2.0

StarRocks analytical DB heads to Linux Foundation
14 February 2023, VentureBeat

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

StarRocks launches managed DBaaS for real-time analytics
14 July 2022, InfoWorld

StarRocks Launches Beta of Cloud Service for Its Analytics Engine
15 July 2022, The New Stack

provided by Google News

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