DBMS > Microsoft Azure Cosmos DB vs. Oracle Coherence vs. PlanetScale vs. Riak KV vs. Rockset

System Properties Comparison Microsoft Azure Cosmos DB vs. Oracle Coherence vs. PlanetScale vs. Riak KV vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Distributed, fault tolerant key-value store

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

Key-value store

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

Document store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

planetscale.com

rockset.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

planetscale.com/docs

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

docs.rockset.com

Developer

Microsoft

Oracle

PlanetScale

OpenSource, formerly Basho Technologies

Rockset

Initial release

2014

2007

2020

2009

2019

Current release

14.1, August 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Java

Erlang

C++

Server operating systems

hosted

All OS with a Java VM

Docker
Linux
macOS

Linux
OS X

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

yes

restricted

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

Read-only SQL queries, including JOINs

APIs and other access methods

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

JCache
JPA
RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

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

.Net
C++
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

yes

proprietary syntax

Erlang

Triggers

JavaScript

yes

Live Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, with selectable consistency level

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

configurable

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

optionally

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 can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

Users with fine-grained authorization concept

no user groups or roles

yes, using Riak Security

Access rights for users and organizations can be defined via Rockset console

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.