DBMS > Databend vs. Drizzle vs. Oracle vs. Sphinx

System Properties Comparison Databend vs. Drizzle vs. Oracle vs. Sphinx

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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.

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Widely used RDBMS

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

Primary database model

Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

github.com/datafuselabs/databend
www.databend.com

www.oracle.com/database

sphinxsearch.com

Technical documentation

docs.databend.com

docs.oracle.com/en/database

sphinxsearch.com/docs

Developer

Databend Labs

Drizzle project, originally started by Brian Aker

Oracle

Sphinx Technologies Inc.

Initial release

2021

2008

1980

2001

Current release

1.0.59, April 2023

7.2.4, September 2012

23c, September 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

restricted free version is available

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

Rust

C++

C and C++

C++

Server operating systems

hosted
Linux
macOS

FreeBSD
Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Proprietary protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Java
PHP

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Users with fine-grained authorization concept, user roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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