DBMS > ArcadeDB vs. Drizzle vs. IRONdb vs. Oracle Coherence vs. Yaacomo

System Properties Comparison ArcadeDB vs. Drizzle vs. IRONdb vs. Oracle Coherence vs. Yaacomo

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.

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Yaacomo seems to be discontinued and is 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 distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Oracles in-memory data grid solution

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

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

Website

arcadedb.com

www.circonus.com/solutions/time-series-database/

www.oracle.com/java/coherence

yaacomo.com

Technical documentation

docs.arcadedb.com

docs.circonus.com/irondb/category/getting-started

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

Developer

Arcade Data

Drizzle project, originally started by Brian Aker

Circonus LLC.

Oracle

Q2WEB GmbH

Initial release

2021

2008

2017

2007

2009

Current release

September 2021

7.2.4, September 2012

V0.10.20, January 2018

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

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++

C and C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

Linux

All OS with a Java VM

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

with proprietary extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

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

JDBC

HTTP API

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

C
C++
Java
PHP

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C++
Java

Server-side scripts

Stored procedures

yes, in Lua

Triggers

hooks for callbacks inside the server can be used.

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware

yes, with selectable consistency level

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

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

authentification to access the cache via certificates or http basic authentication

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

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

Create custom Event Compression Policies in Enterprise Manager to reduce event noise
21 September 2023, Oracle

Microservices with Major New Coherence and Helidon Releases
9 August 2022, Oracle

Nike achieves scalability and performance with Oracle Coherence & Exadata
20 December 2012, Oracle

New solutions for Oracle WebLogic on Azure Virtual Machines
1 April 2021, Microsoft

GridGain: Product Overview and Analysis
5 June 2019, eWeek

provided by Google News

Share this page