DBMS > Apache Impala vs. BaseX vs. Google Cloud Firestore vs. PostgreSQL vs. Yaacomo

System Properties Comparison Apache Impala vs. BaseX vs. Google Cloud Firestore vs. PostgreSQL vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Analytic DBMS for Hadoop

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

impala.apache.org

basex.org

firebase.google.com/products/firestore

www.postgresql.org

yaacomo.com

Technical documentation

impala.apache.org/impala-docs.html

docs.basex.org

firebase.google.com/docs/firestore

www.postgresql.org/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BaseX GmbH

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

Q2WEB GmbH

Initial release

2013

2007

2017

1989

1989: Postgres, 1996: PostgreSQL

2009

Current release

4.1.0, June 2022

10.7, August 2023

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD license

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

Server operating systems

Linux

Linux
OS X
Windows

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

yes, Firebase Rules & Cloud Functions

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

via events

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

yes

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

Users with fine-grained authorization concept on 4 levels

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

More information provided by the system vendor

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