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KairosDB

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44
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Pouchdb

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KairosDB vs Pouchdb: What are the differences?

  1. Data Model: KairosDB uses a time-series data model, optimized for handling large amounts of data indexed by time, making it efficient for time-based queries and analysis. On the other hand, PouchDB is a NoSQL database that stores data in a JSON format, allowing for easier manipulation and querying of data through Javascript functions.

  2. Backends: KairosDB supports a wide range of backend data stores including HBase, Cassandra, InfluxDB, and others, providing flexibility in choosing the most suitable backend for specific needs. In contrast, PouchDB primarily uses IndexedDB as its backend, offering offline storage capabilities and synchronization with CouchDB or other PouchDB instances.

  3. Scalability: KairosDB is more suitable for managing large-scale time-series data with horizontal scalability by distributing data across multiple nodes or clusters, allowing for increased data processing and storage capacity. Conversely, PouchDB is designed for mobile and web applications that require local storage capabilities, making it suitable for scenarios where data sharing and synchronization are not the primary focus.

  4. Querying: KairosDB offers a powerful query language with support for various aggregations, filtering, and downsampling functions that are specifically tailored for time-series data analysis. PouchDB, on the other hand, utilizes Mango queries, which are similar to traditional SQL queries, enabling developers to perform complex data retrievals from the database efficiently.

  5. Concurrency Control: KairosDB provides built-in support for data retention policies, allowing users to define how long data should be stored before being automatically removed, which is crucial for managing storage resources efficiently. In contrast, PouchDB relies on CouchDB's conflict resolution mechanisms, enabling seamless synchronization of data changes across multiple devices or replicas.

  6. Community and Ecosystem: KairosDB has a relatively smaller community and ecosystem compared to PouchDB, which benefits from the larger CouchDB community and extensive plugin ecosystem for additional functionalities and integrations. This difference can influence the availability of resources, documentation, and community support for developers using these databases.

In Summary, KairosDB is optimized for time-series data handling, offers a scalable architecture with diverse backend support, and a powerful query language, while PouchDB excels in local storage for mobile/web applications, utilizes Mango queries, and benefits from a larger community and plugin ecosystem.

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Pros of KairosDB
Pros of Pouchdb
  • 1
    As fast as your cassandra/scylla cluster go
  • 1
    Time-Series data analysis
  • 1
    Easy setup
  • 1
    Easy Rest API
  • 1
    Open source
  • 2
    Offline cache
  • 1
    JSON
  • 1
    Very fast
  • 1
    Free
  • 1
    Repication

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What is KairosDB?

KairosDB is a fast distributed scalable time series database written on top of Cassandra.

What is Pouchdb?

PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.

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What companies use KairosDB?
What companies use Pouchdb?
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What tools integrate with KairosDB?
What tools integrate with Pouchdb?
What are some alternatives to KairosDB and Pouchdb?
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.
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.
Graphite
Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
OpenTSDB
It is a distributed, scalable time series database to store, index & serve metrics collected from computer systems at a large scale. It can store and serve massive amounts of time series data without losing granularity.
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.
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