DBMS > 4D vs. Google BigQuery vs. Memcached vs. Oracle Rdb vs. Sphinx

System Properties Comparison 4D vs. Google BigQuery vs. Memcached vs. Oracle Rdb vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Large scale data warehouse service with append-only tables

In-memory key-value store, originally intended for caching

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

Primary database model

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.4d.com

cloud.google.com/bigquery

www.memcached.org

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

sphinxsearch.com

Technical documentation

developer.4d.com

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

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

sphinxsearch.com/docs

Developer

4D, Inc

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sphinx Technologies Inc.

Initial release

1984

2010

2003

1984

2001

Current release

v20, April 2023

1.6.25, March 2024

7.4.1.1, 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

OS X
Windows

hosted

FreeBSD
Linux
OS X
Unix
Windows

HP Open VMS

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

close to SQL 92

yes

SQL-like query language (SphinxQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP/JSON API

Proprietary protocol

Supported programming languages

4D proprietary IDE
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

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

Multi-source replication

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Since BigQuery is designed for querying data

yes, on a single node

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.

User concepts

Access control

Users and groups

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

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