DBMS > EsgynDB vs. Google Cloud Bigtable vs. IBM Cloudant vs. Oracle Berkeley DB vs. Riak KV

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. IBM Cloudant vs. Oracle Berkeley DB vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Database as a Service offering based on Apache CouchDB

Widely used in-process key-value store

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Key-value store
Wide column store

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.esgyn.cn

cloud.google.com/bigtable

www.ibm.com/products/cloudant

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

cloud.google.com/bigtable/docs

cloud.ibm.com/docs/Cloudant

docs.oracle.com/cd/E17076_05/html/index.html

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Esgyn

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oracle

originally developed by Sleepycat, which was acquired by Oracle

OpenSource, formerly Basho Technologies

Initial release

2015

2010

1994

2009

Current release

18.1.40, May 2020

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache version 2, commercial enterprise edition

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++, Java

Erlang

C, Java, C++ (depending on the Berkeley DB edition)

Erlang

Server operating systems

Linux

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

ADO.NET
JDBC
ODBC

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

RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

View functions (Map-Reduce) in JavaScript

Erlang

Triggers

yes

only for the SQL API

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

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

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Atomic single-row operations

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic 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

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access rights for users can be defined per database

yes, using Riak Security

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Cloudant Best (and Worst) Practices — Part 1
18 March 2019, ibm.com

Intro to Enterprise Cloud Storage: How to Set Up a Cloudant Database
1 December 2014, Linux.com

IBM Expands Cloud Database Services with Kubernetes
26 September 2019, EnterpriseAI

IBM Code Engine and IBM Cloudant: Serverless Data and Infrastructure
16 August 2021, ibm.com

IBM to Purchase Cloudant Database as a service (DBaaS) Provider
22 March 2014, App Developer Magazine

provided by Google News

Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions
26 April 2023, HPCwire

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Margo I. Seltzer | Berkman Klein Center
18 August 2020, Berkman Klein Center

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

Oracle buys Sleepycat Software
14 February 2006, MarketWatch

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

Basho to Bolster Riak with DB Plug-Ins
5 May 2014, Datanami

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Basho launches complete NoSQL software kit - DCD
28 May 2015, DatacenterDynamics

provided by Google News

Share this page