DBMS > EsgynDB vs. Firebolt vs. SWC-DB

System Properties Comparison EsgynDB vs. Firebolt vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Wide column store

Secondary database models

Time Series DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.esgyn.cn

www.firebolt.io

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

Technical documentation

docs.firebolt.io

Developer

Esgyn

Firebolt Analytics Inc.

Alex Kashirin

Initial release

2015

2020

Current release

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPL V3

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++, Java

C++

Server operating systems

Linux

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

.Net
ODBC
RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Go
JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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