DBMS > BoltDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. SWC-DB

System Properties Comparison BoltDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

Time Series DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/boltdb/bolt

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

Developer

Microsoft

Alex Kashirin

Initial release

2013

2014

2012

2020

Current release

2.7.6, April 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

MIT License

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

GPL V3

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

hosted

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API
JSON over UDP

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

RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

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

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

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

C++

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

none

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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

Depending on used storage engine

User concepts

Access control

simple rights management via user accounts

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
» more

News

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 2024

A Detailed Guide to C# TimeSpan
2 May 2024

The Final Frontier: Using InfluxDB on the International Space Station
30 April 2024

Getting the Current Time in C#: A Guide
26 April 2024

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.