DBMS > Apache Impala vs. H2GIS vs. QuestDB vs. Realm vs. VoltDB

System Properties Comparison Apache Impala vs. H2GIS vs. QuestDB vs. Realm vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Spatial extension of H2

A high performance open source SQL database for time series data

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

questdb.io/docs

realm.io/docs

docs.voltdb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CNRS

QuestDB Technology Inc

Realm, acquired by MongoDB in May 2019

VoltDB Inc.

Initial release

2013

2014

2010

Current release

4.1.0, June 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

LGPL 3.0

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

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

Java, C++

Server operating systems

Linux

Linux
macOS
Windows

Android
Backend: server-less
iOS
Windows

Linux
OS X

for development

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL with time-series extensions

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

over HTTP

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

runs within the applications so server-side scripts are unnecessary

Java

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by timestamps)

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

Source-replica replication with eventual consistency

none

Multi-source replication
Source-replica replication

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

ACID for single-table writes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on H2

yes

Users and roles with access to stored procedures

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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8 May 2024

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

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12 April 2024

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

Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB
5 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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Recent citations in the news

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