DBMS > HEAVY.AI vs. JSqlDb vs. OrigoDB vs. SWC-DB

System Properties Comparison HEAVY.AI vs. JSqlDb vs. OrigoDB vs. SWC-DB

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Editorial information provided by DB-Engines

Name

JSqlDB 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

JavaScript Query Language Database, stores JavaScript objects and primitives

A fully ACID in-memory object graph database

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Wide column store

Secondary database models

Spatial DBMS

Time Series 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	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

jsqldb.org (offline)

origodb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.heavy.ai

origodb.com/docs

Developer

HEAVY.AI, Inc.

Konrad von Backstrom

Robert Friberg et al

Alex Kashirin

Initial release

2016

2018

2009

under the name LiveDB

2020

Current release

5.10, January 2022

0.8, December 2018

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL V3

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

C++

Server operating systems

Linux

Linux
macOS
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

.NET Client API
HTTP API
LINQ

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

.Net

C++

Server-side scripts

Stored procedures

functions in JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

using RocksDB

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

Role based authorization

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More resources

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