DBMS > CouchDB vs. Google BigQuery vs. InterSystems Caché vs. ObjectBox vs. Sphinx

System Properties Comparison CouchDB vs. Google BigQuery vs. InterSystems Caché vs. ObjectBox vs. Sphinx

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Large scale data warehouse service with append-only tables

A multi-model DBMS and application server

Extremely fast embedded database for small devices, IoT and Mobile

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

Primary database model

Document store

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Object oriented DBMS

Search engine

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store

Time Series DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

couchdb.apache.org

cloud.google.com/bigquery

www.intersystems.com/products/cache

objectbox.io

sphinxsearch.com

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigquery/docs

docs.intersystems.com

docs.objectbox.io

sphinxsearch.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

InterSystems

ObjectBox Limited

Sphinx Technologies Inc.

Initial release

2005

2010

1997

2017

2001

Current release

3.3.3, December 2023

2018.1.4, May 2020

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache License 2.0

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

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Implementation language

Erlang

C and C++

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

depending on used data model

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

via views

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
RESTful HTTP API

Proprietary native API

Proprietary protocol

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

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
Source-replica replication

Source-replica replication

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

User concepts

Access control

Access rights for users can be defined per database

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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