DBMS > HEAVY.AI vs. OrigoDB vs. Riak KV vs. XTDB

System Properties Comparison HEAVY.AI vs. OrigoDB vs. Riak KV vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A fully ACID in-memory object graph database

Distributed, fault tolerant key-value store

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store

Secondary database models

Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/heavyai/heavydb
www.heavy.ai

origodb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.heavy.ai

origodb.com/docs

www.tiot.jp/riak-docs/riak/kv/latest

www.xtdb.com/docs

Developer

HEAVY.AI, Inc.

Robert Friberg et al

OpenSource, formerly Basho Technologies

Juxt Ltd.

Initial release

2016

2009

under the name LiveDB

2009

2019

Current release

5.10, January 2022

3.2.0, December 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache version 2, commercial enterprise edition

Open Source

MIT License

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++ and CUDA

Erlang

Clojure

Server operating systems

Linux

Linux
Windows

Linux
OS X

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes, extensible-data-notation format

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.

can be achieved using .NET

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
Thrift
Vega

.NET Client API
HTTP API
LINQ

HTTP API
Native Erlang Interface

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Clojure
Java

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

client side managed; servers are not synchronized

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

selectable replication factor

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

depending on model

links between data sets can be stored

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

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

yes, using Riak Security

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More resources

Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Making the most of geospatial intelligence
14 April 2023, InfoWorld

OmniSci Gets HEAVY New Name and New CEO
1 March 2022, Datanami

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

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22 September 2023, InformationWeek

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23 December 2011, InfoQ.com

Basho, Maker of Riak NoSQL Database, Raises $25M
13 January 2015, Data Center Knowledge

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Basho distributes Riak to more customers - DCD
28 November 2013, DatacenterDynamics

provided by Google News

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