DBMS > Apache Spark (SQL) vs. InfluxDB vs. PostgreSQL

System Properties Comparison Apache Spark (SQL) vs. InfluxDB vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Apache Spark SQL is a component on top of 'Spark Core' for structured data processing

DBMS for storing time series, events and metrics

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Secondary database models

Spatial DBMS

with GEO package

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	20.40
Rank	#29	Overall
	#18	Relational DBMS

Score	21.54
Rank	#28	Overall
	#1	Time Series DBMS

Score	667.25
Rank	#4	Overall
	#4	Relational DBMS

Website

spark.apache.org/sql

www.influxdata.com/products/influxdb-overview

www.postgresql.org

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.influxdata.com/influxdb

www.postgresql.org/docs

Developer

Apache Software Foundation

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2014

2013

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.5.0 ( 2.13), September 2023

2.7.6, April 2024

16.4, August 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Scala

Server operating systems

Linux
OS X
Windows

Linux
OS X

through Homebrew

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

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL-like query language

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC

HTTP API
JSON over UDP

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

Supported programming languages

Java
Python
R
Scala

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

Sharding

in enterprise version only

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Depending on used storage engine

User concepts

Access control

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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15 April 2025

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9 April 2025

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