DBMS > Apache Impala vs. DuckDB vs. GeoMesa vs. SiriDB

System Properties Comparison Apache Impala vs. DuckDB vs. GeoMesa vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An embeddable, in-process, column-oriented SQL OLAP RDBMS

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Open Source Time Series DBMS

Primary database model

Relational DBMS

Spatial DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

duckdb.org/docs

www.geomesa.org/documentation/stable/user/index.html

docs.siridb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

CCRi and others

Cesbit

Initial release

2013

2018

2014

2017

Current release

4.1.0, June 2022

1.0.0, June 2024

5.0.1, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

Apache License 2.0

Open Source

MIT License

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++

Scala

Server operating systems

Linux

server-less

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

depending on storage layer

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

depending on storage layer

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

depending on storage layer

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

depending on the DBMS used for storage

simple rights management via user accounts

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

My First Billion (of Rows) in DuckDB
1 May 2024, Towards Data Science

TigerEye Open Sources DuckDB.dart
15 August 2024, Datanami

Unleashing Postgres for Analytics With DuckDB Integration
24 July 2024, The New Stack

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

Reading PCAP Files (Directly) With DuckDB
26 August 2024, Security Boulevard

provided by Google News

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