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Clickhouse

237
307
+ 1
58
InfluxDB

867
888
+ 1
163
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Clickhouse vs InfluxDB: What are the differences?

Developers describe Clickhouse as "A column-oriented database management system". It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query. On the other hand, InfluxDB is detailed as "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..

Clickhouse and InfluxDB belong to "Databases" category of the tech stack.

InfluxDB is an open source tool with 16.7K GitHub stars and 2.39K GitHub forks. Here's a link to InfluxDB's open source repository on GitHub.

Advice on Clickhouse and InfluxDB
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TimescaleDB
MongoDB
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InfluxDB

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

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Replies (3)
Yaron Lavi
Recommends
PostgreSQL

We had a similar challenge. We started with DynamoDB, Timescale, and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us a We had a similar challenge. We started with DynamoDB, Timescale and even InfluxDB and Mongo - to eventually settle with PostgreSQL. Assuming the inbound data pipeline in queued (for example, Kinesis/Kafka -> S3 -> and some Lambda functions), PostgreSQL gave us better performance by far.

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Recommends
Druid

Druid is amazing for this use case and is a cloud-native solution that can be deployed on any cloud infrastructure or on Kubernetes. - Easy to scale horizontally - Column Oriented Database - SQL to query data - Streaming and Batch Ingestion - Native search indexes It has feature to work as TimeSeriesDB, Datawarehouse, and has Time-optimized partitioning.

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Ankit Malik
Software Developer at CloudCover · | 3 upvotes · 65.4K views
Recommends
Google BigQuery

if you want to find a serverless solution with capability of a lot of storage and SQL kind of capability then google bigquery is the best solution for that.

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Decisions about Clickhouse and InfluxDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 51.6K views

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

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Pros of Clickhouse
Pros of InfluxDB
  • 15
    Fast, very very fast
  • 10
    Good compression ratio
  • 5
    Horizontally scalable
  • 4
    RESTful
  • 4
    Utilizes all CPU resources
  • 4
    Great CLI
  • 3
    Has no transactions
  • 3
    Great number of SQL functions
  • 2
    Buggy
  • 2
    Open-source
  • 1
    In IDEA data import via HTTP interface not working
  • 1
    Server crashes its normal :(
  • 1
    Highly available
  • 1
    Flexible compression options
  • 1
    Flexible connection options
  • 1
    ODBC
  • 51
    Time-series data analysis
  • 28
    Easy setup, no dependencies
  • 24
    Fast, scalable & open source
  • 21
    Open source
  • 18
    Real-time analytics
  • 6
    Continuous Query support
  • 5
    Easy Query Language
  • 4
    HTTP API
  • 4
    Out-of-the-box, automatic Retention Policy
  • 1
    Offers Enterprise version
  • 1
    Free Open Source version

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Cons of Clickhouse
Cons of InfluxDB
  • 2
    Slow insert operations
  • 4
    Instability
  • 1
    HA or Clustering is only in paid version

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- No public GitHub repository available -

What is Clickhouse?

It allows analysis of data that is updated in real time. It offers instant results in most cases: the data is processed faster than it takes to create a query.

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.

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What companies use Clickhouse?
What companies use InfluxDB?
See which teams inside your own company are using Clickhouse or InfluxDB.
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What tools integrate with Clickhouse?
What tools integrate with InfluxDB?

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What are some alternatives to Clickhouse and InfluxDB?
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.
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).
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.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
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.
See all alternatives