DBMS > Apache Phoenix vs. Vertica

System Properties Comparison Apache Phoenix vs. Vertica

Please select another system to include it in the comparison.

Our visitors often compare Apache Phoenix and Vertica with MySQL, PostgreSQL and Hive.

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

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	2.97
Rank	#106	Overall
	#55	Relational DBMS

Score	20.13
Rank	#37	Overall
	#23	Relational DBMS

Website

phoenix.apache.org

www.vertica.com

Technical documentation

phoenix.apache.org

vertica.com/documentation

Developer

Apache Software Foundation

Micro Focus

prior to that Hewlett Packard

Initial release

2014

2005

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

11.1, February 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

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

Typing

predefined data types such as float or date

yes

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

yes

No Indexes Required

SQL

Support of SQL

yes

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

APIs and other access methods

JDBC

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

character-based, interactive, front-end utility

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C#
C++
Java
Perl
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

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

Hadoop integration

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

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 (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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...
» more

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

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

DB-Engines blog posts

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

show all

Recent citations in the news

Apache Spark vs Apache Hadoop: Compare data science tools
26 May 2022, TechRepublic

Apache Phoenix Now HBase 2.0 Compatible
20 July 2018, iProgrammer

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

HPE gobbles up Ampool to add SQL grunt to Ezmeral
9 July 2021, The Register

Hadoop 101: HBase and Client Access
16 February 2017, DZone

provided by Google News

Enterprise Database Management System (DBMS) Market Analysis, Research Study With Oracle Corporation, Microsoft Corporation, IBM Corporation
16 August 2022, Digital Journal

Vertica Announces Vertica 12 for Future-Proof Analytics
7 June 2022, PR Newswire

Partitioning for performance in a sharding database system
2 August 2022, InfoWorld

Cloudian Partners with Vertica to Deliver On-Premises Data Warehouse Platform on S3 Data Lake
28 June 2022, GlobeNewswire

Cloudian Partners with Vertica to Deliver On-prem Data Warehouse Platform on S3 Data Lake
28 June 2022, Datanami

provided by Google News

Job opportunities

Solutions Architect
Cloudera, Virginia

Data Engineer ll - Core Technology Infrastructure
Bank of America, Richmond, VA

Solutions Consultant
Cloudera, Maryland

Senior Full Stack Software Developer in Test
Amiseq, Milpitas, CA

Distributed Big Data Platform Engineer
Bloomberg, New York, NY

ETL Developer (Healthcare) - 100% Remote
Piper Companies, Remote

Database Consultant
Brilliant Infotech, Dundee, FL

Database Administrator
Maxpro, Albany, NY

Database Engineer
Millennium Management LLC, Miami, FL

Systems Software Engineer at Vertica (REMOTE / WORK FROM HOME)
Micro Focus, Cambridge, MA

jobs by

Share this page