DBMS > Apache Impala vs. OushuDB vs. Realm vs. Warp 10

System Properties Comparison Apache Impala vs. OushuDB vs. Realm vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

impala.apache.org

www.oushu.com/product/oushuDB

realm.io

www.warp10.io

Technical documentation

impala.apache.org/impala-docs.html

www.oushu.com/documentation

realm.io/docs

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Oushu

Realm, acquired by MongoDB in May 2019

SenX

Initial release

2013

2014

2015

Current release

4.1.0, June 2022

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache License 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++

Java

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C
C++

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

runs within the applications so server-side scripts are unnecessary

yes

WarpScript

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

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

In-Memory realm

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Kerberos, SSL and role based access

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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Recent citations in the news

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