InfluxDB vs PostGIS

Overview

InfluxDB

Stacks1.0K

Followers1.2K

Votes175

PostGIS

Stacks381

Followers377

Votes30

GitHub Stars2.0K

Forks407

InfluxDB vs PostGIS: What are the differences?

Data Type Support: InfluxDB is optimized for time series data and provides native support for time-related data types such as timestamps and durations. PostGIS, on the other hand, offers specialized support for various spatial data types like points, lines, and polygons.
Query Capabilities: InfluxDB comes with its query language, InfluxQL, which is tailored for time series data manipulation and analysis. PostGIS, on the other hand, leverages SQL (Structured Query Language) which allows for more generalized querying including spatial functions and operators.
Indexing and Retrieval: InfluxDB uses a time-based index to efficiently store and retrieve time series data, making it ideal for applications that deal with large volumes of time-stamped data. PostGIS utilizes spatial indexes like R-Tree or GIST to accelerate spatial queries and operations on geometric objects.
Scalability: InfluxDB is horizontally scalable, meaning it can handle increasing data loads by adding more nodes to the cluster. PostGIS, being an extension of PostgreSQL, inherits its scalability features, allowing for vertical scaling through better hardware or sharding.
Use Cases: InfluxDB is commonly used in monitoring applications, IoT (Internet of Things) devices, and DevOps tools where real-time analytics and metrics are crucial. PostGIS, on the other hand, finds its applications in spatial analysis, geographic information systems (GIS), routing, and mapping services.
Community and Ecosystem: InfluxDB has a strong community focused on time series data processing and analysis tools. PostGIS benefits from the vast PostgreSQL ecosystem and community support which provides a wide range of extensions and plugins for various use cases.

In Summary, InfluxDB is optimized for time series data with support for time-related data types and efficient time-based indexing, while PostGIS is tailored for spatial data processing with specialized spatial data types, SQL querying, and spatial indexing capabilities.

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Advice on InfluxDB, PostGIS

Anonymous

Apr 21, 2020

Needs advice

We are building an IOT service with heavy write throughput and fewer reads (we need downsampling records). We prefer to have good reliability when comes to data and prefer to have data retention based on policies.

So, we are looking for what is the best underlying DB for ingesting a lot of data and do queries easily

381k views381k

Comments

Benoit

Principal Engineer at Sqreen

Sep 21, 2019

Decided

I chose TimescaleDB because to be the backend system of our production monitoring system. We needed to be able to keep track of multiple high cardinality dimensions.

The drawbacks of this decision are our monitoring system is a bit more ad hoc than it used to (New Relic Insights)

We are combining this with Grafana for display and Telegraf for data collection

155k views155k

Comments

pionell

Sep 16, 2020

Needs adviceon

MariaDB

I have a lot of data that's currently sitting in a MariaDB database, a lot of tables that weigh 200gb with indexes. Most of the large tables have a date column which is always filtered, but there are usually 4-6 additional columns that are filtered and used for statistics. I'm trying to figure out the best tool for storing and analyzing large amounts of data. Preferably self-hosted or a cheap solution. The current problem I'm running into is speed. Even with pretty good indexes, if I'm trying to load a large dataset, it's pretty slow.

159k views159k

Comments

Detailed Comparison

InfluxDB	PostGIS
InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.	PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL.
Time-Centric Functions;Scalable Metrics; Events;Native HTTP API;Powerful Query Language;Built-in Explorer	Processing and analytic functions for both vector and raster data for splicing, dicing, morphing, reclassifying, and collecting/unioning with the power of SQL;raster map algebra for fine-grained raster processing;Spatial reprojection SQL callable functions for both vector and raster data;Support for importing / exporting ESRI shapefile vector data via both commandline and GUI packaged tools and support for more formats via other 3rd-party Open Source tools
Statistics
GitHub Stars -	GitHub Stars 2.0K
GitHub Forks -	GitHub Forks 407
Stacks 1.0K	Stacks 381
Followers 1.2K	Followers 377
Votes 175	Votes 30
Pros & Cons
Pros 59 Time-series data analysis 30 Easy setup, no dependencies 24 Fast, scalable & open source 21 Open source 20 Real-time analytics Cons 4 Instability 1 Proprietary query language 1 HA or Clustering is only in paid version	Pros 25 De facto GIS in SQL 5 Good Documentation
Integrations
No integrations available	PostgreSQL

What are some alternatives to InfluxDB, PostGIS?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

Related Comparisons

InfluxDB vs PostGIS: What are the differences?

Data Type Support: InfluxDB is optimized for time series data and provides native support for time-related data types such as timestamps and durations. PostGIS, on the other hand, offers specialized support for various spatial data types like points, lines, and polygons.
Query Capabilities: InfluxDB comes with its query language, InfluxQL, which is tailored for time series data manipulation and analysis. PostGIS, on the other hand, leverages SQL (Structured Query Language) which allows for more generalized querying including spatial functions and operators.
Indexing and Retrieval: InfluxDB uses a time-based index to efficiently store and retrieve time series data, making it ideal for applications that deal with large volumes of time-stamped data. PostGIS utilizes spatial indexes like R-Tree or GIST to accelerate spatial queries and operations on geometric objects.
Scalability: InfluxDB is horizontally scalable, meaning it can handle increasing data loads by adding more nodes to the cluster. PostGIS, being an extension of PostgreSQL, inherits its scalability features, allowing for vertical scaling through better hardware or sharding.
Use Cases: InfluxDB is commonly used in monitoring applications, IoT (Internet of Things) devices, and DevOps tools where real-time analytics and metrics are crucial. PostGIS, on the other hand, finds its applications in spatial analysis, geographic information systems (GIS), routing, and mapping services.
Community and Ecosystem: InfluxDB has a strong community focused on time series data processing and analysis tools. PostGIS benefits from the vast PostgreSQL ecosystem and community support which provides a wide range of extensions and plugins for various use cases.

InfluxDB vs PostGIS

Overview