DBMS > BigchainDB vs. CockroachDB vs. Couchbase vs. Memcached vs. Microsoft Access

System Properties Comparison BigchainDB vs. CockroachDB vs. Couchbase vs. Memcached vs. Microsoft Access

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

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.)

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

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

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

www.bigchaindb.com

www.cockroachlabs.com

www.couchbase.com

www.memcached.org

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

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.cockroachlabs.com/docs

docs.couchbase.com

github.com/memcached/memcached/wiki

developer.microsoft.com/en-us/access

Developer

Cockroach Labs

Couchbase, Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Initial release

2016

2015

2011

2003

1992

Current release

23.1.1, May 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.6.25, March 2024

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0, commercial license available

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

BSD license

commercial

Bundled with Microsoft Office

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

Python

C, C++, Go and Erlang

C++

Server operating systems

Linux

Linux
macOS
Windows

Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

Windows

Not a real database server, but making use of DLLs

Data scheme

schema-free

dynamic 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

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

but not compliant to any SQL standard

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Proprietary protocol

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

since Access 2010 using the ACE-engine

Triggers

yes

via the TAP protocol

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Automatic Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using RAFT

Multi-source replication

including cross data center replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

but no files for transaction logging

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

yes

Role-based access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

yes

using SASL (Simple Authentication and Security Layer) protocol

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

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