DBMS > Apache Impala vs. QuestDB vs. Riak TS vs. SAP HANA

System Properties Comparison Apache Impala vs. QuestDB vs. Riak TS vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A high performance open source SQL database for time series data

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store

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	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

impala.apache.org

questdb.io

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

questdb.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

QuestDB Technology Inc

Open Source, formerly Basho Technologies

SAP

Initial release

2013

2014

2015

2010

Current release

4.1.0, June 2022

3.0.0, September 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

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.

Implementation language

C++

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

Erlang

Server operating systems

Linux

Linux
macOS
Windows

Linux
OS X

Appliance or cloud-service

Data scheme

yes

schema-free via InfluxDB Line Protocol

schema-free

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL with time-series extensions

yes, limited

yes

APIs and other access methods

JDBC
ODBC

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

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

over HTTP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

SQLScript, R

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with eventual consistency

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

ACID for single-table writes

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

through memory mapped files

yes

User concepts

Access control

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

QuestDB 8.0: Major Release
23 May 2024

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8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

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