DBMS > Hypertable vs. OrientDB vs. RisingWave vs. RocksDB

System Properties Comparison Hypertable vs. OrientDB vs. RisingWave vs. RocksDB

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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

Multi-model DBMS (Document, Graph, Key/Value)

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

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

Primary database model

Wide column store

Document store
Graph DBMS
Key-value store

Relational DBMS

Key-value store

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

orientdb.org

www.risingwave.com/database

rocksdb.org

Technical documentation

www.orientdb.com/docs/last/index.html

docs.risingwave.com/docs/current/intro

github.com/facebook/rocksdb/wiki

Developer

Hypertable Inc.

OrientDB LTD; CallidusCloud; SAP

RisingWave Labs

Facebook, Inc.

Initial release

2009

2010

2022

2013

Current release

0.9.8.11, March 2016

3.2.29, March 2024

1.2, September 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

BSD

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

Rust

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

All OS with a Java JDK (>= JDK 6)

Docker
Linux
macOS

Linux

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

schema-free

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

C++ API
Thrift

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

JDBC
PostgreSQL wire protocol

C++ API
Java API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Java, Javascript

UDFs in Python or Java

Triggers

Hooks

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

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

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

Access rights for users and roles; record level security configurable

Users and Roles

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