DBMS > Blueflood vs. EDB Postgres vs. Hive vs. Yaacomo

System Properties Comparison Blueflood vs. EDB Postgres vs. Hive vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable TimeSeries DBMS based on Cassandra

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

blueflood.io

www.enterprisedb.com

hive.apache.org

yaacomo.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.enterprisedb.com/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

Rackspace

EnterpriseDB

Apache Software Foundation

initially developed by Facebook

Q2WEB GmbH

Initial release

2013

2005

2012

2009

Current release

14, December 2021

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2

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

Server operating systems

Linux
OS X

Linux
Windows

All OS with a Java VM

Android
Linux
Windows

Data scheme

predefined scheme

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP REST

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

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

by hash, list or range

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual 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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

EDB unveils EDB Postgres AI
23 May 2024, InfoWorld

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack
22 April 2024, Datanami

Nutanix partners with EDB to fit database service for AI – Blocks and Files
21 May 2024, Blocks and Files

Enterprise DB begins rolling AI features into PostgreSQL
23 May 2024, SiliconANGLE News

EDB Announces EDB Postgres® AI, an Intelligent Platform for Transactional, Analytical and AI Workloads
23 May 2024, GlobeNewswire

provided by Google News

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

GC Tuning for Improved Presto Reliability
11 January 2024, Uber

provided by Google News

Share this page