DBMS > BigObject vs. Drizzle vs. Machbase Neo vs. Oracle Rdb vs. Sphinx

System Properties Comparison BigObject vs. Drizzle vs. Machbase Neo vs. Oracle Rdb vs. Sphinx

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

Analytic DBMS for real-time computations and queries

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

TimeSeries DBMS for AIoT and BigData

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

bigobject.io

machbase.com

www.oracle.com/database/technologies/related/rdb.html

sphinxsearch.com

Technical documentation

docs.bigobject.io

machbase.com/dbms

www.oracle.com/database/technologies/related/rdb-doc.html

sphinxsearch.com/docs

Developer

BigObject, Inc.

Drizzle project, originally started by Brian Aker

Machbase

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sphinx Technologies Inc.

Initial release

2015

2008

2013

1984

2001

Current release

7.2.4, September 2012

V8.0, August 2023

7.4.1.1, 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

GNU GPL

commercial

free test version available

commercial

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

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
macOS
Windows

HP Open VMS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Proprietary protocol

Supported programming languages

C
C++
Java
PHP

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Lua

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

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More resources

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