DBMS > Blueflood vs. Drizzle vs. Hazelcast vs. Oracle Coherence

System Properties Comparison Blueflood vs. Drizzle vs. Hazelcast vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A widely adopted in-memory data grid

Oracles in-memory data grid solution

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

blueflood.io

hazelcast.com

www.oracle.com/java/coherence

Technical documentation

github.com/rax-maas/blueflood/wiki

hazelcast.org/imdg/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Rackspace

Drizzle project, originally started by Brian Aker

Hazelcast

Oracle

Initial release

2013

2008

2007

Current release

7.2.4, September 2012

5.3.6, November 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses 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

Server operating systems

Linux
OS X

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

predefined scheme

yes

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

HTTP REST

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

hooks for callbacks inside the server can be used.

yes

Events

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

Replicated Map

yes, with selectable consistency level

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

authentification to access the cache via certificates or http basic authentication

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