DBMS > atoti vs. IBM Db2 Event Store vs. YugabyteDB

System Properties Comparison atoti vs. IBM Db2 Event Store vs. YugabyteDB

Please select another system to include it in the comparison.

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

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Object oriented DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

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

Score	0.47
Rank	#251	Overall
	#12	Object oriented DBMS

Score	0.19
Rank	#313	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	2.45
Rank	#107	Overall
	#53	Relational DBMS

Website

atoti.io

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

www.yugabyte.com

Technical documentation

docs.atoti.io

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

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

ActiveViam

IBM

Yugabyte Inc.

Initial release

2017

Current release

2.0

2.19, September 2023

License

Commercial or Open Source

commercial

free versions available

commercial

free developer edition available

Open Source

Apache 2.0

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

Java

C and C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

Data scheme

yes

depending on used data model

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

Multidimensional Expressions (MDX)

yes

through the embedded Spark runtime

yes, PostgreSQL compatible

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

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 (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

Python

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

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

based on RocksDB

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Overview Of Atoti: A Python BI Analytics Tool
14 May 2021, AIM

ActiveViam Announces Leadership Succession
4 September 2024, Business Wire

provided by Google News

Mudhakar Srivatsa
18 November 2024, IBM Research

Best cloud databases of 2022
4 October 2022, ITPro

How IBM Is Turning Db2 into an ‘AI Database’
3 June 2019, Datanami

provided by Google News

Yugabyte Announces Sixth Annual Distributed SQL Summit, Unveils Keynote and Lineup of Speakers for November Hybrid Event
3 October 2024, Business Wire

YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale
19 September 2024, SiliconANGLE News

YugabyteDB on AWS Graviton: The Winning Combination for Distributed SQL Developers
15 November 2024, AWS Blog

YugabyteDB Evolves PostgreSQL to a Distributed Architecture for Modern, Cloud-Native Applications
19 September 2024, Business Wire

Simplifying cloud-native app development with Yugabyte
2 August 2024, IMDA

provided by Google News

Share this page