DBMS > BigObject vs. H2 vs. Quasardb vs. SWC-DB

System Properties Comparison BigObject vs. H2 vs. Quasardb vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed, high-performance timeseries database

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series 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	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

bigobject.io

www.h2database.com

quasar.ai

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

Technical documentation

docs.bigobject.io

www.h2database.com/html/main.html

doc.quasar.ai/master

Developer

BigObject, Inc.

Thomas Mueller

quasardb

Alex Kashirin

Initial release

2015

2005

2009

2020

Current release

2.2.220, July 2023

3.14.1, January 2024

0.5, April 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Java

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

yes

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

HTTP API

Proprietary protocol
Thrift

Supported programming languages

Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C++

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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