DBMS > Drizzle vs. Hazelcast vs. Hyprcubd vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Hazelcast vs. Hyprcubd vs. Microsoft Azure Table Storage

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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.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

A widely adopted in-memory data grid

Serverless Time Series DBMS

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Website

hazelcast.com

hyprcubd.com (offline)

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

hazelcast.org/imdg/docs

Developer

Drizzle project, originally started by Brian Aker

Hazelcast

Hyprcubd, Inc.

Microsoft

Initial release

2008

2012

Current release

7.2.4, September 2012

5.3.6, November 2023

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC (https)

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

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

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

hooks for callbacks inside the server can be used.

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Replicated Map

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

token access

Access rights based on private key authentication or shared access signatures

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More resources

DB-Engines blog posts

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