DBMS > IBM Db2 Event Store vs. SurrealDB vs. SWC-DB vs. Valentina Server

System Properties Comparison IBM Db2 Event Store vs. SurrealDB vs. SWC-DB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A fully ACID transactional, developer-friendly, multi-model DBMS

A high performance, scalable Wide Column DBMS

Object-relational database and reports server

Primary database model

Event Store
Time Series DBMS

Document store
Graph DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

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

surrealdb.com

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

www.valentina-db.net

Technical documentation

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

surrealdb.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

IBM

SurrealDB Ltd

Alex Kashirin

Paradigma Software

Initial release

2017

2022

2020

1999

Current release

2.0

v1.5.0, May 2024

0.5, April 2021

5.7.5

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Rust

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

GraphQL
RESTful HTTP API
WebSocket

Proprietary protocol
Thrift

ODBC

Supported programming languages

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

Deno
Go
JavaScript (Node.js)
Rust

C++

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

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

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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