DBMS > Blueflood vs. EsgynDB vs. Postgres-XL vs. XTDB

System Properties Comparison Blueflood vs. EsgynDB vs. Postgres-XL vs. XTDB

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

blueflood.io

www.esgyn.cn

www.postgres-xl.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.postgres-xl.org/documentation

www.xtdb.com/docs

Developer

Rackspace

Esgyn

Juxt Ltd.

Initial release

2013

2015

2014

since 2012, originally named StormDB

2019

Current release

10 R1, October 2018

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Open Source

MIT License

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

Clojure

Server operating systems

Linux
OS X

Linux

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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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