DBMS > HBase vs. Vertica

System Properties Comparison HBase vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Cloud or on-premises 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

Wide column store

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	39.34
Rank	#26	Overall
	#2	Wide column stores

Score	18.01
Rank	#38	Overall
	#23	Relational DBMS

Website

hbase.apache.org

www.vertica.com

Technical documentation

hbase.apache.org

vertica.com/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Micro Focus

prior to that Hewlett Packard

Initial release

2008

2005

Current release

2.3.4, January 2021

11.1, February 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

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.

Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.

Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

schema-free, schema definition possible

yes, but unstructured data can be stored in specific Flex-Tables

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY

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

No Indexes Required

SQL

Support of SQL

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

APIs and other access methods

Java API
RESTful HTTP API
Thrift

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

character-based, interactive, front-end utility

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Java
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

Coprocessors in Java

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

Multi-source replication
Source-replica replication

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

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more

Competitive advantages

Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

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23 January 2023, Medium

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Review: HBase is massively scalable -- and hugely complex
31 March 2014, InfoWorld

A Look At HBase, the NoSQL Database Built on Hadoop
6 May 2015, The New Stack

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11 January 2023, Forbes

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28 June 2022, GlobeNewswire

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19 April 2022, VentureBeat

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24 January 2023, Digital Journal

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