DBMS > ArcadeDB vs. BigObject vs. Drizzle vs. EsgynDB vs. Kinetica

System Properties Comparison ArcadeDB vs. BigObject vs. Drizzle vs. EsgynDB vs. Kinetica

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

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

Analytic DBMS for real-time computations and queries

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Fully vectorized database across both GPUs and CPUs

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

Technical documentation

docs.arcadedb.com

docs.bigobject.io

docs.kinetica.com

Developer

Arcade Data

BigObject, Inc.

Drizzle project, originally started by Brian Aker

Esgyn

Kinetica

Initial release

2021

2015

2008

2015

2012

Current release

September 2021

7.2.4, September 2012

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

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++, Java

C, C++

Server operating systems

All OS with a Java VM

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

Linux

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

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

fluentd
ODBC
RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

GPU vRAM or System RAM

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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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

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