DBMS > Hypertable vs. RocksDB vs. Ultipa

System Properties Comparison Hypertable vs. RocksDB vs. Ultipa

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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

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Wide column store

Key-value store

Graph DBMS

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

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

rocksdb.org

www.ultipa.com

Technical documentation

github.com/facebook/rocksdb/wiki

www.ultipa.com/document

Developer

Hypertable Inc.

Facebook, Inc.

Ultipa

Initial release

2009

2013

2019

Current release

0.9.8.11, March 2016

9.2.1, May 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

APIs and other access methods

C++ API
Thrift

C++ API
Java API

RESTful HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

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

yes

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

User concepts

Access control

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