DBMS > IBM Db2 Event Store vs. InfluxDB vs. MySQL vs. NSDb vs. Snowflake

System Properties Comparison IBM Db2 Event Store vs. InfluxDB vs. MySQL vs. NSDb vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

DBMS for storing time series, events and metrics

Widely used open source RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.ibm.com/products/db2-event-store

www.influxdata.com/products/influxdb-overview

www.mysql.com

nsdb.io

www.snowflake.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

docs.influxdata.com/influxdb

dev.mysql.com/doc

nsdb.io/Architecture

docs.snowflake.net/manuals/index.html

Developer

IBM

Oracle

since 2010, originally MySQL AB, then Sun

Snowflake Computing Inc.

Initial release

2017

2013

1995

2017

2014

Current release

2.0

2.7.6, April 2024

8.4.0, April 2024

License

Commercial or Open Source

commercial

free developer edition available

Open Source

MIT-License; commercial enterprise version available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

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.

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Implementation language

C and C++

Java, Scala

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

through Homebrew

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
JSON over UDP

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
HTTP REST
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

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

Java
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

Using Apache Lucene

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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