DBMS > IBM Db2 warehouse vs. OpenTenBase vs. Vertica

System Properties Comparison IBM Db2 warehouse vs. OpenTenBase vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Cloud-based data warehousing service

An enterprise-level distributed HTAP open source database based on PostgreSQL

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.25
Rank	#164	Overall
	#75	Relational DBMS

Score	0.00
Rank	#392	Overall
	#158	Relational DBMS

Score	9.53
Rank	#42	Overall
	#26	Relational DBMS

Website

www.ibm.com/products/db2/warehouse

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

www.vertica.com

Technical documentation

docs.opentenbase.org
docs.opentenbase.org/en

vertica.com/documentation

Developer

IBM

OpenAtom Foundation, previously Tencent

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2014

2005

Current release

2.5, January 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

BSD-3

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

hosted

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

Import/export of XML data possible

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
Go
Java
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

Recent citations in the news

A major upgrade to Db2® Warehouse on IBM Cloud®
16 October 2024, IBM

Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on, mission-critical workloads
11 July 2023, IBM

Data Mining in Db2 Warehouse: the basics
23 June 2020, Towards Data Science

Top 7 Cloud Data Warehouse Companies
31 May 2023, Datamation

Tackling AI’s data challenges with IBM databases on AWS
14 March 2024, IBM

provided by Google News

New browser-based query editor for OpenText Core Analytics Database accelerates and simplifies querying your data
25 November 2024, blogs.opentext.com

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK
11 February 2021, AWS Blog

Solving Big Data Challenges with Data Science at Uber
20 March 2019, Uber

What’s New in OpenText Vertica
10 January 2024, blogs.opentext.com

provided by Google News

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