Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

InfluxDB
InfluxDB

529
399
+ 1
121
Kafka
Kafka

4.9K
4.4K
+ 1
488
Add tool

InfluxDB vs Kafka: What are the differences?

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.; Kafka: Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

InfluxDB can be classified as a tool in the "Databases" category, while Kafka is grouped under "Message Queue".

Some of the features offered by InfluxDB are:

  • Time-Centric Functions
  • Scalable Metrics
  • Events

On the other hand, Kafka provides the following key features:

  • Written at LinkedIn in Scala
  • Used by LinkedIn to offload processing of all page and other views
  • Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)

"Time-series data analysis" is the primary reason why developers consider InfluxDB over the competitors, whereas "High-throughput" was stated as the key factor in picking Kafka.

InfluxDB and Kafka are both open source tools. It seems that InfluxDB with 16.7K GitHub stars and 2.39K forks on GitHub has more adoption than Kafka with 12.7K GitHub stars and 6.81K GitHub forks.

Uber Technologies, Spotify, and Slack are some of the popular companies that use Kafka, whereas InfluxDB is used by trivago, Redox Engine, and Thumbtack. Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to InfluxDB, which is listed in 119 company stacks and 39 developer stacks.

What is InfluxDB?

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.

What is Kafka?

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Get Advice Icon

Need advice about which tool to choose?Ask the StackShare community!

Why do developers choose InfluxDB?
Why do developers choose Kafka?

Sign up to add, upvote and see more prosMake informed product decisions

What companies use InfluxDB?
What companies use Kafka?

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with InfluxDB?
What tools integrate with Kafka?

Sign up to get full access to all the tool integrationsMake informed product decisions

What are some alternatives to InfluxDB and Kafka?
TimescaleDB
TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
Redis
Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
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.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
See all alternatives
Decisions about InfluxDB and Kafka
Roman Bulgakov
Roman Bulgakov
Senior Back-End Developer, Software Architect at Chemondis GmbH · | 3 upvotes · 10.5K views
Kafka
Kafka

I use Kafka because it has almost infinite scaleability in terms of processing events (could be scaled to process hundreds of thousands of events), great monitoring (all sorts of metrics are exposed via JMX).

Downsides of using Kafka are: - you have to deal with Zookeeper - you have to implement advanced routing yourself (compared to RabbitMQ it has no advanced routing)

See more
Kafka
Kafka
RabbitMQ
RabbitMQ

The question for which Message Queue to use mentioned "availability, distributed, scalability, and monitoring". I don't think that this excludes many options already. I does not sound like you would take advantage of Kafka's strengths (replayability, based on an even sourcing architecture). You could pick one of the AMQP options.

I would recommend the RabbitMQ message broker, which not only implements the AMQP standard 0.9.1 (it can support 1.x or other protocols as well) but has also several very useful extensions built in. It ticks the boxes you mentioned and on top you will get a very flexible system, that allows you to build the architecture, pick the options and trade-offs that suite your case best.

For more information about RabbitMQ, please have a look at the linked markdown I assembled. The second half explains many configuration options. It also contains links to managed hosting and to libraries (though it is missing Python's - which should be Puka, I assume).

See more
Frédéric MARAND
Frédéric MARAND
Core Developer at OSInet · | 2 upvotes · 121.3K views
atOSInetOSInet
Beanstalkd
Beanstalkd
RabbitMQ
RabbitMQ
Kafka
Kafka

I used Kafka originally because it was mandated as part of the top-level IT requirements at a Fortune 500 client. What I found was that it was orders of magnitude more complex ...and powerful than my daily Beanstalkd , and far more flexible, resilient, and manageable than RabbitMQ.

So for any case where utmost flexibility and resilience are part of the deal, I would use Kafka again. But due to the complexities involved, for any time where this level of scalability is not required, I would probably just use Beanstalkd for its simplicity.

I tend to find RabbitMQ to be in an uncomfortable middle place between these two extremities.

See more
Interest over time
Reviews of InfluxDB and Kafka
Review ofInfluxDBInfluxDB

Influx doesn't currently natively support horizontal distribution. Hard to recommend it until they implement that.

Avatar of YaronWittenstein
Computer Science
Review ofInfluxDBInfluxDB

InfluxDB is a game changer

How developers use InfluxDB and Kafka
Avatar of Pinterest
Pinterest uses KafkaKafka

http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.

Avatar of ShadowICT
ShadowICT uses InfluxDBInfluxDB

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.

Avatar of Coolfront Technologies
Coolfront Technologies uses KafkaKafka

Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

Avatar of Goyoboard
Goyoboard uses InfluxDBInfluxDB

To track time-series of course, utilizing few retention rules and continuous queries to keep time-series data fast and maintanable

Avatar of sapslaj
sapslaj uses InfluxDBInfluxDB

InfluxDB ingests information from various sources (mostly Telegraf instances) into one place for monitoring purposes.

Avatar of ShareThis
ShareThis uses KafkaKafka

We are using Kafka as a message queue to process our widget logs.

Avatar of Chris Hartwig
Chris Hartwig uses InfluxDBInfluxDB

All our metrics go through InfluxDB, both applicative and system

Avatar of Christopher Davison
Christopher Davison uses KafkaKafka

Used for communications and triggering jobs across ETL systems

Avatar of theskyinflames
theskyinflames uses KafkaKafka

Used as a integration middleware by messaging interchanging.

How much does InfluxDB cost?
How much does Kafka cost?
Pricing unavailable
Pricing unavailable