DBMS > BoltDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Riak TS

System Properties Comparison BoltDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Riak TS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Globally distributed, horizontally scalable, multi-model database service

Multi-model DBMS (Document, Graph, Key/Value)

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

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

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

github.com/boltdb/bolt

azure.microsoft.com/services/cosmos-db

orientdb.org

Technical documentation

learn.microsoft.com/azure/cosmos-db

www.orientdb.com/docs/last/index.html

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

Developer

Microsoft

OrientDB LTD; CallidusCloud; SAP

Open Source, formerly Basho Technologies

Initial release

2013

2014

2010

2015

Current release

3.2.29, March 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache version 2

Open Source

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java JDK (>= JDK 6)

Linux
OS X

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

restricted

SQL

Support of SQL

SQL-like query language

SQL-like query language, no joins

yes, limited

APIs and other access methods

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

JavaScript

Java, Javascript

Erlang

Triggers

JavaScript

Hooks

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

links between datasets can be stored

Transaction concepts

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

yes

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.

User concepts

Access control

Access rights can be defined down to the item level

Access rights for users and roles; record level security configurable

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.