DBMS > Apache Druid vs. Infobright vs. Vertica

System Properties Comparison Apache Druid vs. Infobright vs. Vertica

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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
Time Series DBMS

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	3.10
Rank	#106	Overall
	#53	Relational DBMS
	#7	Time Series DBMS

Score	1.57
Rank	#171	Overall
	#80	Relational DBMS

Score	13.88
Rank	#42	Overall
	#27	Relational DBMS

Website

druid.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.vertica.com

Technical documentation

druid.apache.org/docs/latest/design

vertica.com/documentation

Developer

Apache Software Foundation and contributors

Ignite Technologies Inc.; formerly InfoBright Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2005

Current release

27.0.0, August 2023

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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 SaaS.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux

Data scheme

yes

schema-less columns are supported

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.

Secondary indexes

yes

Knowledge Grid Technology used instead

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

SQL

Support of SQL

SQL for querying

yes

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

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

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

character-based, interactive, front-end utility

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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 off-cloud,...
» 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

Recent citations in the news

InfluxDB Clustered targets on-premises time-series database deployments
6 September 2023, InfoWorld

The Basics of Event-Driven Architectures
22 September 2023, The New Stack

Change Data Capture for Real-Time Access to Backend Databases
5 September 2023, The New Stack

What's 'Pipeline-Free' Real-Time Data Analytics?
5 September 2023, The New Stack

Apache Druid Charms in Upper Echelons of OLAP Database ...
3 April 2023, Datanami

provided by Google News

IBM Bolsters Database Security with Guardium 12.0
27 September 2023, IT Jungle

The 28 Best Enterprise Data Management Software for 2023
26 September 2023, Solutions Review

Vertica by OpenText and Anritsu Sign New Deal for Next-Gen ...
17 May 2023, PR Newswire

Vertica Database to Reward Open Source Developers via New ...
2 November 2022, Datanami

Database Management Software Market 2023-2031 with Scope and Trend
15 September 2023, Benzinga

provided by Google News

Job opportunities

Software Engineer
Capgemini, California

GCP Druid Sr. Engineer
Intone Networks, Irving, TX

Systems Analyst Manager
DeepIntent, New York, NY

Database Administrator – R01529365
Brillio, Dallas, TX

Lead Streaming Engineer
U.S. Bank National Association, Cupertino, CA

Cloud Data Infrastructure Specialist
Publicis Sapient, Chicago, IL

Vertica Data Engineer - Data Migration
Infobahn Solutions Inc., Remote

Redhat Linux Consultant
Cloud Shift Technologies LLC, Columbus, OH

Talend ETL developer
Sledding Technologies, Remote

Senior Associate Data Engineer
Publicis Sapient, New York, NY

jobs by

Share this page