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Pouchdb

116
216
+ 1
6
TimescaleDB

177
295
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41
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Pouchdb vs TimescaleDB: What are the differences?

Developers describe Pouchdb as "Open-source JavaScript database inspired by Apache CouchDB that's designed to run well within the browser". 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. On the other hand, TimescaleDB is detailed as "Scalable time-series database optimized for fast ingest and complex queries. Purpose-built as a PostgreSQL extension". TimescaleDB is the only open-source time-series database that natively supports full-SQL at scale, combining the power, reliability, and ease-of-use of a relational database with the scalability typically seen in NoSQL databases.

Pouchdb and TimescaleDB can be categorized as "Databases" tools.

Some of the features offered by Pouchdb are:

  • Cross browser compatibility
  • Lightweight
  • Easy to learn

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

  • Packaged as a PostgreSQL extension
  • Full ANSI SQL
  • JOINs (e.g., across PostgreSQL tables)

Pouchdb and TimescaleDB are both open source tools. It seems that Pouchdb with 12.1K GitHub stars and 1.21K forks on GitHub has more adoption than TimescaleDB with 7.28K GitHub stars and 385 GitHub forks.

WakaTime, ScreenAware, and AgFlow are some of the popular companies that use TimescaleDB, whereas Pouchdb is used by BrightMachine, Greenkeeper, and SearchBookGo, LLC.. TimescaleDB has a broader approval, being mentioned in 15 company stacks & 3 developers stacks; compared to Pouchdb, which is listed in 8 company stacks and 9 developer stacks.

Advice on Pouchdb and TimescaleDB
Umair Iftikhar
Technical Architect at ERP Studio · | 3 upvotes · 208.8K views
Needs advice
on
TimescaleDBTimescaleDBDruidDruid
and
CassandraCassandra

Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

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Replies (1)
Recommends
MongoDBMongoDB

Hi Umair, Did you try MongoDB. We are using MongoDB on a production environment and collecting data from devices like your scenario. We have a MongoDB cluster with three replicas. Data from devices are being written to the master node and real-time dashboard UI is using the secondary nodes for read operations. With this setup write operations are not affected by read operations too.

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Needs advice
on
TimescaleDBTimescaleDBMongoDBMongoDB
and
InfluxDBInfluxDB

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
PostgreSQLPostgreSQL

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
DruidDruid

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 · 143.6K views
Recommends
Google BigQueryGoogle 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 Pouchdb and TimescaleDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 75.4K 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 Pouchdb
Pros of TimescaleDB
  • 2
    Offline cache
  • 1
    JSON
  • 1
    Very fast
  • 1
    Free
  • 1
    Repication
  • 8
    Open source
  • 7
    Easy Query Language
  • 6
    Time-series data analysis
  • 5
    Established postgresql API and support
  • 4
    Reliable
  • 2
    Postgres integration
  • 2
    Fast and scalable
  • 2
    High-performance
  • 2
    Chunk-based compression
  • 2
    Paid support for automatic Retention Policy
  • 1
    Case studies

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Cons of Pouchdb
Cons of TimescaleDB
    Be the first to leave a con
    • 5
      Licensing issues when running on managed databases

    Sign up to add or upvote consMake informed product decisions

    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.

    What is 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.

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    What companies use Pouchdb?
    What companies use TimescaleDB?
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    What tools integrate with Pouchdb?
    What tools integrate with TimescaleDB?

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    What are some alternatives to Pouchdb and TimescaleDB?
    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.
    SQLite
    SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
    CouchDB
    Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
    Firebase
    Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds.
    Hoodie
    We want to enable you to build complete web apps in days, without having to worry about backends, databases or servers, all with an open source library that's as simple to use as jQuery.
    See all alternatives