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Platform

InfluxDB enables real-time analytics by serving as a purpose-built database that optimizes processing and scaling

InfluxDB 3.0 Overview

Better ingest performance, sub-second queries, and lower storage costs

Integrations

300+ plugins for easy interoperability

Use with popular client libraries, tools, and open source projects

Easy Data Collection

Telegraf collects data from 300+ technologies using open source

See performance comparison

In the Cloud

InfluxDB Cloud Serverless

For startups and small teams
Start small, pay for what you use

InfluxDB Cloud Dedicated

For enterprises and organizations
Dedicated resources, scale, and advanced security

On-Prem

InfluxDB Clustered

For enterprises and organizations
Scale, enterprise features, control where you run

Find the right product

InfluxDB by Use Cases

Network monitoring IoT Monitoring and Analytics SaaS Operational Monitoring

InfluxDB by Industries

Manufacturing Telecommunications Energy and Utilities

InfluxDB Customers

Customers Become an InfluxDB Inventor

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Options for running InfluxDB on AWS

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Nga Tran

Nga Tran

Nga Tran is a staff software engineer at InfluxData and a member of the company’s IOx team, which is building the next-generation time series storage engine for InfluxDB. Before InfluxData, Nga worked at Vertica Systems where she was one of the key engineers who built the query optimizer for Vertica and later ran Vertica’s engineering team. In her spare time, Nga enjoys writing and posting materials for building distributed databases on her blog.

Making Most Recent Value Queries Hundreds of Times Faster

This post explains how databases optimize queries, which can result in queries running hundreds of times faster. While we focus on one specific query type that is important to InfluxDB 3.0, the optimization process we describe is the same for any...

How to read InfluxDB 3.0 Query Plans

This blog post explains how to read a query plan in InfluxDB 3.0 and requires basic knowledge of InfluxDB 3.0 System Architecture. InfluxDB 3.0 supports two query languages: SQL and InfluxQL. The database executes a query written in either SQL or...

Partitioning Data for Query Performance in InfluxDB 3.0

Query performance is critical in any database. Data partitioning is a mechanism that helps prune unnecessary data, allowing queries to run faster. However, there are always trade-offs between large and small numbers of partitions. For instance, fine-grained partitioning on high cardinality...

InfluxDB 3.0: System Architecture

InfluxDB 3.0 (previously known as InfluxDB IOx) is a (cloud) scalable database that offers high performance for both data loading and querying, and focuses on time series use cases. This article describes the system architecture of the database. Figure 1 shows...

Compactor: A Hidden Engine of Database Performance

This article was originally published in InfoWorld and is reposted here with permission. The compactor handles critical post-ingestion and pre-query workloads in the background on a separate server, enabling low latency for data ingestion and high performance for queries. The demand...

Using Deduplication for Eventually Consistent Transactions

This article was originally published in InfoWorld and is reposted here with permission. Deduplication is an effective alternative to transactions for eventually consistent use cases of a distributed database. Here’s why. Building a distributed database is complicated and needs to consider...

Partitioning for Performance in a Sharding Database System

This article was originally published in InfoWorld and is reposted here with permission. Partitioning can provide a number of benefits to a sharding system, including faster query execution. Let’s see how it works. In a previous post, I described a sharding...

Scaling Throughput and Performance in a Sharding Database System

This article was originally published in InfoWorld and is reposted here with permission. Understand the two dimensions of scaling for database query and ingest workloads, and how sharding can make scaling elastic — or not. Scaling throughput and performance are critical...

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