DBMS > Drizzle vs. Heroic vs. Oracle Coherence vs. Quasardb

System Properties Comparison Drizzle vs. Heroic vs. Oracle Coherence vs. Quasardb

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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

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Oracles in-memory data grid solution

Distributed, high-performance timeseries database

Primary database model

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

github.com/spotify/heroic

www.oracle.com/java/coherence

quasar.ai

Technical documentation

spotify.github.io/heroic

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

doc.quasar.ai/master

Developer

Drizzle project, originally started by Brian Aker

Spotify

Oracle

quasardb

Initial release

2008

2014

2007

2009

Current release

7.2.4, September 2012

14.1, August 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

via Elasticsearch

yes

with tags

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JCache
JPA
RESTful HTTP API

HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

yes, with selectable consistency level

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

authentification to access the cache via certificates or http basic authentication

Cryptographically strong user authentication and audit trail

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