DBMS > IBM Db2 Event Store vs. Machbase Neo vs. RavenDB vs. SwayDB

System Properties Comparison IBM Db2 Event Store vs. Machbase Neo vs. RavenDB vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

TimeSeries DBMS for AIoT and BigData

Open Source Operational and Transactional Enterprise NoSQL Document Database

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Document store

Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
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	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

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

machbase.com

ravendb.net

swaydb.simer.au

Technical documentation

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

machbase.com/dbms

ravendb.net/docs

Developer

IBM

Machbase

Hibernating Rhinos

Simer Plaha

Initial release

2017

2013

2010

2018

Current release

2.0

V8.0, August 2023

5.4, July 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

free test version available

Open Source

AGPL version 3, commercial license available

Open Source

GNU Affero GPL V3.0

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++

Scala

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
macOS
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

SQL-like query language (RQL)

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID, Cluster-wide transaction available

Atomic execution of operations

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

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Authorization levels configured per client per database

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