DBMS > Apache Impala vs. Realm vs. Sequoiadb vs. SQream DB

System Properties Comparison Apache Impala vs. Realm vs. Sequoiadb vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

NewSQL database with distributed OLTP and SQL

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store

Document store
Relational DBMS

Relational 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	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

realm.io/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.sqream.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Realm, acquired by MongoDB in May 2019

Sequoiadb Ltd.

SQream Technologies

Initial release

2013

2014

2013

2017

Current release

4.1.0, June 2022

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Server: AGPL; Client: Apache V2

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes, ANSI Standard SQL Types

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

proprietary protocol using JSON

.Net
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C++
Java
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

runs within the applications so server-side scripts are unnecessary

JavaScript

user defined functions in Python

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

simple password-based access control

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More resources

DB-Engines blog posts

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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

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24 June 2022, InfoWorld

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

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27 October 2017, KDnuggets

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15 October 2017, Fossbytes

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9 February 2024, insideBIGDATA

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5 October 2023, FierceWireless

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

Chinese giant Alibaba leads investment round in Israel big-data startup
30 May 2018, The Times of Israel

Accelerated Databases In The Fast Lane
25 June 2020, The Next Platform

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