DBMS > Apache Kylin vs. Hypertable vs. Realm vs. ReductStore

System Properties Comparison Apache Kylin vs. Hypertable vs. Realm vs. ReductStore

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

kylin.apache.org

realm.io

github.com/reductstore
www.reduct.store

Technical documentation

kylin.apache.org/docs

realm.io/docs

www.reduct.store/docs

Developer

Apache Software Foundation, originally contributed from eBay Inc

Hypertable Inc.

Realm, acquired by MongoDB in May 2019

ReductStore LLC

Initial release

2015

2009

2014

2023

Current release

3.1.0, July 2020

0.9.8.11, March 2016

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

Open Source

Business Source License 1.1

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

Java

C++

C++, Rust

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Android
Backend: server-less
iOS
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

C++ API
Thrift

HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

User concepts

Access control

yes

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