DBMS > Alibaba Cloud Table Store vs. Cloudflare Workers KV vs. Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Yaacomo

System Properties Comparison Alibaba Cloud Table Store vs. Cloudflare Workers KV vs. Microsoft Azure Cosmos DB vs. Oracle Berkeley DB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Globally distributed, horizontally scalable, multi-model database service

Widely used in-process key-value store

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Wide column store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

www.alibabacloud.com/product/table-store

www.cloudflare.com/developer-platform/workers-kv

azure.microsoft.com/services/cosmos-db

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

yaacomo.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

developers.cloudflare.com/kv/api

learn.microsoft.com/azure/cosmos-db

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

Developer

Alibaba

Cloudflare

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Q2WEB GmbH

Initial release

2016

2018

2014

1994

2009

Current release

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

commercial

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

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL interfaced based on SQLite is available

yes

APIs and other access methods

HTTP API

HTTP REST
Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

Supported programming languages

Java
Python

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.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

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

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

Access rights based on subaccounts and tokens

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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