DBMS > EsgynDB vs. Greenplum vs. Interbase vs. Snowflake vs. Transwarp StellarDB

System Properties Comparison EsgynDB vs. Greenplum vs. Interbase vs. Snowflake vs. Transwarp StellarDB

Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Light-weight proven RDBMS

originally from Borland

Cloud-based data warehousing service for structured and semi-structured data

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	3.78
Rank	#77	Overall
	#41	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

www.esgyn.cn

greenplum.org

www.embarcadero.com/products/interbase

www.snowflake.com

www.transwarp.cn/en/product/stellardb

Technical documentation

docs.greenplum.org

docs.embarcadero.com/products/interbase

docs.snowflake.net/manuals/index.html

Developer

Esgyn

Pivotal Software Inc.

Embarcadero

Snowflake Computing Inc.

Transwarp

Initial release

2015

2005

1984

2014

Current release

7.0.0, September 2023

InterBase 2020, December 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

Server operating systems

Linux

Android
iOS
Linux
OS X
Windows

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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

since Version 4.2

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

OpenCypher

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Interbase procedure and trigger language

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

Interbase Change Views

yes

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

Multiversion concurreny control

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

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