DBMS > BigchainDB vs. Couchbase vs. HarperDB vs. Tkrzw

System Properties Comparison BigchainDB vs. Couchbase vs. HarperDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

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

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store

Key-value store

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	0.76
Rank	#216	Overall
	#36	Document stores

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.couchbase.com

docs.harperdb.io/docs

Developer

Couchbase, Inc.

HarperDB

Mikio Hirabayashi

Initial release

2016

2011

2017

2020

Current release

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

3.1, August 2021

0.9.3, August 2020

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

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

commercial

free community edition available

Open Source

Apache Version 2.0

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

Node.js

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X

Linux
macOS

Data scheme

schema-free

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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

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

SQL-like data manipulation statements

APIs and other access methods

CLI Client
RESTful HTTP API

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

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

Custom Functions

since release 3.1

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

including cross data center replication
Source-replica replication

yes

the nodes on which a table resides can be defined

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

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

using specific database classes

User concepts

Access control

yes

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

Access rights for users and roles

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