DBMS > atoti vs. IBM Db2 Event Store vs. Oracle vs. ReductStore

System Properties Comparison atoti vs. IBM Db2 Event Store vs. Oracle vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Distributed Event Store optimized for Internet of Things use cases

Widely used RDBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Object oriented DBMS

Event Store
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

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

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

atoti.io

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

www.oracle.com/database

github.com/reductstore
www.reduct.store

Technical documentation

docs.atoti.io

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

docs.oracle.com/en/database

www.reduct.store/docs

Developer

ActiveViam

IBM

Oracle

ReductStore LLC

Initial release

2017

1980

2023

Current release

2.0

23c, September 2023

1.9, March 2024

License

Commercial or Open Source

commercial

free versions available

commercial

free developer edition available

commercial

restricted free version is available

Open Source

Business Source License 1.1

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

Java

C and C++

C++, Rust

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Docker
Linux
macOS
Windows

Data scheme

yes

Schemaless in JSON and XML columns

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through the embedded Spark runtime

yes

with proprietary extensions

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Python

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

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