DBMS > Apache Impala vs. HBase vs. OrigoDB

System Properties Comparison Apache Impala vs. HBase vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Wide-column store based on Apache Hadoop and on concepts of BigTable

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Wide column store

Document store
Object oriented DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

impala.apache.org

hbase.apache.org

origodb.com

Technical documentation

impala.apache.org/impala-docs.html

hbase.apache.org/book.html

origodb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Robert Friberg et al

Initial release

2013

2008

2009

under the name LiveDB

Current release

4.1.0, June 2022

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

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

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

Linux
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Coprocessors in Java

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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 rights for users, groups and roles

based on Apache Sentry and Kerberos

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Role based authorization

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Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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

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20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

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22 December 2022, Built In

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24 February 2023, Simplilearn

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