DBMS > ArcadeDB vs. Drizzle vs. Hazelcast vs. Teradata Aster

System Properties Comparison ArcadeDB vs. Drizzle vs. Hazelcast vs. Teradata Aster

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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.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

A widely adopted in-memory data grid

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

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

Website

arcadedb.com

hazelcast.com

Technical documentation

docs.arcadedb.com

hazelcast.org/imdg/docs

Developer

Arcade Data

Drizzle project, originally started by Brian Aker

Hazelcast

Teradata

Initial release

2021

2008

2005

Current release

September 2021

7.2.4, September 2012

5.3.6, November 2023

License

Commercial or Open Source

Open Source

Apache Version 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

All OS with a Java VM

FreeBSD
Linux
OS X

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Java

C
C++
Java
PHP

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

R packages

Triggers

hooks for callbacks inside the server can be used.

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

Replicated Map

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

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

ACID

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
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