DBMS > Apache Impala vs. MaxDB vs. MySQL vs. QuestDB vs. SAP HANA

System Properties Comparison Apache Impala vs. MaxDB vs. MySQL vs. QuestDB vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A robust and reliable RDBMS optimized to run all major SAP solutions

Widely used open source RDBMS

A high performance open source SQL database for time series data

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	2.65
Rank	#111	Overall
	#55	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

maxdb.sap.com/documentation

dev.mysql.com/doc

questdb.io/docs

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

since 2010, originally MySQL AB, then Sun

QuestDB Technology Inc

SAP

Initial release

2013

1984

1995

2014

2010

Current release

4.1.0, June 2022

7.9.10.12, February 2024

8.3.0, January 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Limited community edition free

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

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

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL with time-series extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
JDBC
ODBC
Proprietary native API

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

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Java
Perl
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

over HTTP

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by timestamps)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication with eventual consistency

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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

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