DBMS > IBM Db2 Event Store vs. Snowflake vs. SWC-DB vs. YottaDB

System Properties Comparison IBM Db2 Event Store vs. Snowflake vs. SWC-DB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

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

A high performance, scalable Wide Column DBMS

A fast and solid embedded Key-value store

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Wide column store

Key-value store

Secondary database models

Time Series DBMS

Relational DBMS

using the Octo plugin

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	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

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

www.snowflake.com

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

yottadb.com

Technical documentation

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

docs.snowflake.net/manuals/index.html

yottadb.com/resources/documentation

Developer

IBM

Snowflake Computing Inc.

Alex Kashirin

YottaDB, LLC

Initial release

2017

2014

2020

2001

Current release

2.0

0.5, April 2021

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

GPL V3

Open Source

AGPL 3.0

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 and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

Linux

Docker
Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

SQL-like query language

by using the Octo plugin

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

JavaScript (Node.js)
Python

C++

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard 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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Users and groups based on OS-security mechanisms

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