DBMS > EsgynDB vs. Heroic vs. PostGIS vs. SWC-DB

System Properties Comparison EsgynDB vs. Heroic vs. PostGIS vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Spatial extension of PostgreSQL

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Relational DBMS

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	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.esgyn.cn

github.com/spotify/heroic

postgis.net

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

Technical documentation

spotify.github.io/heroic

postgis.net/documentation

Developer

Esgyn

Spotify

Alex Kashirin

Initial release

2015

2014

2005

2020

Current release

3.4.2, February 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL v2.0

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++, Java

Java

C++

Server operating systems

Linux

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Proprietary protocol
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

based on PostgreSQL

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
Immediate Consistency

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

yes

based on PostgreSQL

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page