Apache Flink vs InfluxDB: What are the differences?
What is Apache Flink? Fast and reliable large-scale data processing engine. Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
What is InfluxDB? An open-source distributed time series database with no external dependencies. 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..
Apache Flink and InfluxDB are primarily classified as "Big Data" and "Databases" tools respectively.
Some of the features offered by Apache Flink are:
- Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
- Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
- Flexible and expressive windowing semantics for data stream programs
On the other hand, InfluxDB provides the following key features:
- Time-Centric Functions
- Scalable Metrics
"Unified batch and stream processing" is the top reason why over 6 developers like Apache Flink, while over 35 developers mention "Time-series data analysis" as the leading cause for choosing InfluxDB.
Apache Flink and InfluxDB are both open source tools. InfluxDB with 16.6K GitHub stars and 2.37K forks on GitHub appears to be more popular than Apache Flink with 9.11K GitHub stars and 4.86K GitHub forks.
According to the StackShare community, InfluxDB has a broader approval, being mentioned in 116 company stacks & 38 developers stacks; compared to Apache Flink, which is listed in 20 company stacks and 21 developer stacks.
What is Apache Flink?
What is InfluxDB?
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We use InfluxDB as a store for our data that gets fed into Grafana. It's ideal for this as it's a lightweight storage engine that can be modified on the fly by scripts without having to log into the server itself and manage tables. The HTTP API also makes it ideal for integrating with frontend services.
To track time-series of course, utilizing few retention rules and continuous queries to keep time-series data fast and maintanable
InfluxDB ingests information from various sources (mostly Telegraf instances) into one place for monitoring purposes.