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

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

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Cassandra and DynamoDB compatible wide column store

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

A high performance, scalable Wide Column DBMS

Primary database model

Event Store
Time Series DBMS

Wide column store

Relational DBMS

Wide column store

Secondary database models

Key-value store

Time Series 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	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

www.scylladb.com

www.snowflake.com

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

Technical documentation

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

docs.scylladb.com

docs.snowflake.net/manuals/index.html

Developer

IBM

ScyllaDB

Snowflake Computing Inc.

Alex Kashirin

Initial release

2017

2015

2014

2020

Current release

2.0

ScyllaDB Open Source 5.4.1, January 2024

0.5, April 2021

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Open Source (AGPL), commercial license available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux

hosted

Linux

Data scheme

yes

schema-free

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

yes

cluster global secondary indices

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like DML and DDL statements (CQL)

yes

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

yes

yes, Lua

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

selectable replication factor

Representation of geographical distribution of servers is possible

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

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

in-memory tables

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

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

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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