DBMS > IBM Db2 Event Store vs. Oracle NoSQL vs. QuestDB vs. Riak KV

System Properties Comparison IBM Db2 Event Store vs. Oracle NoSQL vs. QuestDB vs. Riak KV

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A high performance open source SQL database for time series data

Distributed, fault tolerant key-value store

Primary database model

Event Store
Time Series DBMS

Document store
Key-value store
Relational DBMS

Time Series DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Relational DBMS

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	2.81
Rank	#98	Overall
	#7	Time Series DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

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

www.oracle.com/database/nosql/technologies/nosql

questdb.io

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

questdb.io/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

IBM

Oracle

QuestDB Technology Inc

OpenSource, formerly Basho Technologies

Initial release

2017

2011

2014

2009

Current release

2.0

24.1, May 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

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++

Java

Java (Zero-GC), C++, Rust

Erlang

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Linux
OS X

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free via InfluxDB Line Protocol

schema-free

Typing

predefined data types such as float or date

yes

optional

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

restricted

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like DML and DDL statements

SQL with time-series extensions

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

HTTP API
Native Erlang Interface

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication with eventual consistency

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID for single-table writes

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

off heap cache

yes

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes, using Riak Security

More information provided by the system vendor

News

Combine Java and Rust Code Coverage in a Polyglot Project
10 September 2024

Weather data visualization and forecasting with QuestDB, Kafka and Grafana
4 September 2024

Building a new vector based storage model
22 August 2024

Calibrating VWAP executions with QuestDB and Grafana
16 August 2024

Write Time: a call for community writers
13 August 2024

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

Mudhakar Srivatsa
11 December 2023, IBM Research

Best cloud databases of 2022
4 October 2022, ITPro

IBM Confronts AI Resistance
23 October 2019, RTInsights

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

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

provided by Google News

OpenWorld 2013: Oracle NoSQL Database On the Rise?
13 December 2023, Channel Futures

Cloud database comparison: AWS, Microsoft, Google and Oracle
24 July 2024, TechTarget

Top 8 Best NoSQL Databases in 2024
9 September 2024, AIM

Explore Oracle Database Solutions for Maximum Efficiency
4 September 2018, Oracle

NoSQL Rebels Aim Missile at Larry Ellison's Yacht
20 July 2012, WIRED

provided by Google News

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

QuestDB gets $12M Series A funding amid growing interest in time-series databases
3 November 2021, SiliconANGLE News

Read the Pitch Deck Database Startup QuestDB Used to Raise $12 Million
11 November 2021, Business Insider

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

provided by Google News

Basho Revamps Riak Open-Source Database
22 September 2023, InformationWeek

A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

Is Riak A Good NoSQL Database Option For Enterprises?
1 July 2019, AIM

Basho aims for enterprise operational simplicity with new Data Platform
26 May 2015, diginomica

provided by Google News

Share this page