DBMS > CouchDB vs. Google Cloud Bigtable vs. Microsoft Access vs. Redis vs. RocksDB

System Properties Comparison CouchDB vs. Google Cloud Bigtable vs. Microsoft Access vs. Redis vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Key-value store
Wide column store

Relational DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Key-value store

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

couchdb.apache.org

cloud.google.com/bigtable

www.microsoft.com/en-us/microsoft-365/access

redis.com
redis.io

rocksdb.org

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigtable/docs

developer.microsoft.com/en-us/access

docs.redis.com/latest/index.html
redis.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

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

Google

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Facebook, Inc.

Initial release

2005

2015

1992

2009

2013

Current release

3.3.3, December 2023

1902 (16.0.11328.20222), March 2019

7.2.4, January 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Open Source

BSD

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Windows

Not a real database server, but making use of DLLs

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

via views

yes

with RediSearch module

SQL

Support of SQL

yes

but not compliant to any SQL standard

with RediSQL module

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
DAO
ODBC
OLE DB

proprietary protocol

RESP - REdis Serialization Protocol

C++ API
Java API

Supported programming languages

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

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes

since Access 2010 using the ACE-engine

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

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

Atomic single-row operations

ACID

but no files for transaction logging

Atomic execution of command blocks and scripts and optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

a simple user-level security was built in till version Access 2003

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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