DBMS > Blueflood vs. EsgynDB vs. GridDB vs. Transwarp StellarDB

System Properties Comparison Blueflood vs. EsgynDB vs. GridDB vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Scalable in-memory time series database optimized for IoT and Big Data

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

blueflood.io

www.esgyn.cn

griddb.net

www.transwarp.cn/en/product/stellardb

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.griddb.net

Developer

Rackspace

Esgyn

Toshiba Corporation

Transwarp

Initial release

2013

2015

2013

Current release

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

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++, Java

C++

Server operating systems

Linux
OS X

Linux

Data scheme

predefined scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

OpenCypher

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

yes

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