DBMS > Amazon Redshift vs. InfluxDB vs. OpenQM vs. RocksDB vs. Vertica

System Properties Comparison Amazon Redshift vs. InfluxDB vs. OpenQM vs. RocksDB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

DBMS for storing time series, events and metrics

QpenQM is a high-performance, self-tuning, multi-value DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Column oriented

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/redshift

www.influxdata.com/products/influxdb-overview

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

rocksdb.org

www.vertica.com

Technical documentation

docs.aws.amazon.com/redshift

docs.influxdata.com/influxdb

github.com/facebook/rocksdb/wiki

vertica.com/documentation

Developer

Amazon (based on PostgreSQL)

Rocket Software, originally Martin Phillips

Facebook, Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2013

1993

2013

2005

Current release

2.7.6, April 2024

3.4-12

9.2.1, May 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

GPLv2, extended commercial license available

Open Source

BSD

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
OS X

through Homebrew

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

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

Numeric data and Strings

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.

yes

Secondary indexes

restricted

yes

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

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

APIs and other access methods

JDBC
ODBC

HTTP API
JSON over UDP

C++ API
Java API

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

character-based, interactive, front-end utility

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

yes

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

yes

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

Depending on used storage engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

Access rights can be defined down to the item level

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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