DBMS > Couchbase vs. Google Cloud Bigtable vs. Graphite vs. HBase vs. InfluxDB

System Properties Comparison Couchbase vs. Google Cloud Bigtable vs. Graphite vs. HBase vs. InfluxDB

Editorial information provided by DB-Engines

Name

Description

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

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Wide-column store based on Apache Hadoop and on concepts of BigTable

DBMS for storing time series, events and metrics

Primary database model

Document store

Key-value store
Wide column store

Time Series DBMS

Wide column store

Time Series DBMS

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

Spatial DBMS

with GEO package

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

www.couchbase.com

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

hbase.apache.org

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.couchbase.com

cloud.google.com/bigtable/docs

graphite.readthedocs.io

hbase.apache.org/book.html

docs.influxdata.com/influxdb

Developer

Couchbase, Inc.

Google

Chris Davis

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2011

2015

2006

2008

2013

Current release

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

2.3.4, January 2021

2.7.6, April 2024

License

Commercial or Open Source

Open Source

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

commercial

Open Source

Apache 2.0

Open Source

Apache version 2

Open Source

MIT-License; commercial enterprise version 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, C++, Go and Erlang

Python

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux
Unix

Linux
Unix
Windows

using Cygwin

Linux
OS X

through Homebrew

Data scheme

schema-free

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

options to bring your own types, AVRO

Numeric data and Strings

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 query language

APIs and other access methods

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

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

HTTP API
Sockets

Java API
RESTful HTTP API
Thrift

HTTP API
JSON over UDP

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

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

yes

Coprocessors in Java

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

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

none

Multi-source replication
Source-replica replication

selectable replication factor

in enterprise version only

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

none

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-row operations

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

Depending on used storage engine

User concepts

Access control

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

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple rights management via user accounts

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