DBMS > atoti vs. Blueflood vs. Cassandra vs. Greenplum

System Properties Comparison atoti vs. Blueflood vs. Cassandra vs. Greenplum

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Scalable TimeSeries DBMS based on Cassandra

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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.

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store
Spatial DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Website

Technical documentation

docs.atoti.io

github.com/rax-maas/blueflood/wiki

cassandra.apache.org/doc/latest

docs.greenplum.org

Developer

ActiveViam

Rackspace

Apache Software Foundation

Apache top level project, originally developped by Facebook

Pivotal Software Inc.

Initial release

2013

2008

2005

Current release

4.1.3, July 2023

7.0.0, September 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

Linux
OS X

BSD
Linux
OS X
Windows

Linux

Data scheme

predefined scheme

schema-free

yes

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

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

HTTP REST

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
Java
Perl
Python
R

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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