DBMS > Apache Impala vs. Dolt vs. HyperSQL vs. Prometheus

System Properties Comparison Apache Impala vs. Dolt vs. HyperSQL vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A MySQL compatible DBMS with Git-like versioning of data and schema

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

impala.apache.org

github.com/dolthub/dolt
www.dolthub.com

hsqldb.org

prometheus.io

Technical documentation

impala.apache.org/impala-docs.html

docs.dolthub.com

hsqldb.org/web/hsqlDocsFrame.html

prometheus.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DoltHub Inc

Initial release

2013

2018

2001

2015

Current release

4.1.0, June 2022

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

Linux

Linux
macOS
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

All languages supporting JDBC/ODBC
Java

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

currently in alpha release

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

none

yes

by Federation

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

none

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Only one user is configurable, and must be specified in the config file at startup

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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