DBMS > HEAVY.AI vs. Hyprcubd vs. OrigoDB vs. SwayDB

System Properties Comparison HEAVY.AI vs. Hyprcubd vs. OrigoDB vs. SwayDB

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

A fully ACID in-memory object graph database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

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

hyprcubd.com (offline)

origodb.com

swaydb.simer.au

Technical documentation

docs.heavy.ai

origodb.com/docs

Developer

HEAVY.AI, Inc.

Hyprcubd, Inc.

Robert Friberg et al

Simer Plaha

Initial release

2016

2009

under the name LiveDB

2018

Current release

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

Scala

Server operating systems

Linux

hosted

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

User defined using .NET types and collections

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift
Vega

gRPC (https)

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

token access

Role based authorization

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More resources

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provided by Google News

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