DBMS > Amazon Redshift vs. Apache Impala vs. QuestDB vs. Solr

System Properties Comparison Amazon Redshift vs. Apache Impala vs. QuestDB vs. Solr

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

A high performance open source SQL database for time series data

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Document store

Relational DBMS

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/redshift

impala.apache.org

questdb.io

solr.apache.org

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

questdb.io/docs

solr.apache.org/resources.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

QuestDB Technology Inc

Apache Software Foundation

Initial release

2012

2013

2014

2006

Current release

4.1.0, June 2022

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java (Zero-GC), C++, Rust

Java

Server operating systems

hosted

Linux

Linux
macOS
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL with time-series extensions

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

ACID for single-table writes

optimistic locking

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

through memory mapped files

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

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23 May 2024

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8 May 2024

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6 May 2024

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12 April 2024

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