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IndexedDB vs InfluxDB: What are the differences?
# Differences Between IndexedDB and InfluxDB
IndexedDB and InfluxDB are two popular databases that serve different purposes in the tech world.
Here are some key differences between IndexedDB and InfluxDB:
1. **Database Type**: IndexedDB is a client-side database which means it runs in the user's browser, while InfluxDB is server-side database designed for handling time-series data efficiently.
2. **Data Model**: IndexedDB follows a key-value pair data model and is mainly used for storing structured data, whereas InfluxDB is optimized for storing timestamped data and metadata.
3. **Query Language**: IndexedDB uses a more traditional querying language similar to SQL for data retrieval and manipulation, whereas InfluxDB uses its own query language specifically tailored for time-series data known as InfluxQL.
4. **Use Case**: IndexedDB is commonly used in web applications for client-side storage and caching, while InfluxDB is preferred for IoT and monitoring applications where time-series data is prevalent.
5. **Scalability**: InfluxDB is designed to handle high volumes of time-series data efficiently with features like data retention policies and continuous queries, making it more scalable for large datasets compared to IndexedDB.
6. **Community Support**: IndexedDB has solid support within the web development community due to its native browser integration, while InfluxDB enjoys popularity within the IoT and DevOps communities for its specialized time-series data handling capabilities.
In Summary, IndexedDB and InfluxDB differ in their database type, data model, query language, use cases, scalability, and community support, catering to distinct needs in the database ecosystem.
I'm currently developing an app that ranks trending stuff ( such as games, memes or movies, etc. ) or events in a particular country or region. Here are the specs: My app does not require registration and requires cookies and localStorage to track users. Users can add new entries to each trending category provided that their country of origin is recorded in cookies. If each category contains more than 100 items then the oldest items get deleted. The question is: what kind of database should I use for managing this app? Thanks in advance
I think your best and cheapest choice is going to be MongoDB, Although Postgres is probably going to be the more scaleable approach, you likely have a good idea of how you want to present your data, and the app seems small enough that you shouldn't need to worry about scaling issues. It also sounds like your app can grow in a linear capacity based on the number of users, and the amount of data, which is the perfect use-case for noSQL databases (linear, predictable scaling).
Correct me if I have any of these assumptions wrong. 1. You're looking to have a relatively high-read with a lower write volume 2. Your app is essentially a list of objects that can belong to a category 3. users can create objects in this list.
I think Mongo is going to be what you're looking for on the following basis: 1. you absolutely need a database that is shared by all users of your app, therefor IndexedDB is out of the question. 2. You have semi-structured data 3. you probably want the cheapest solution.
I think Postgres is wrong for the following reasons: 1. your app is pretty simple in concept, SQL databases will add unnecessary complexity to your system, either through ORMs or SQL queries. (use an ORM if you go with SQL) 2. Hosting SQL databases for production is not cheap! the cheapest solution I know of for Postgres is ElephantSQL. It provides 20MB for free with 5 concurrent connections, you should be okay to manage these limitations if you decide to go Postgres in the end. Whereas mongoDB Atlas has some great free-tier options.
Although your data might be easier to model in Postgres, you can certainly model your data as a single list of items that have a category attached.
I don't want to officially recommend another tool, but you should really checkout prisma, firebase, amplify, or Azure App Services for this app! Just go completely backend-less [Firebase] https://firebase.google.com/ [Amplify] https://aws.amazon.com/amplify/ [Prisma] https://www.prisma.io/ [Azure App Services] https://azure.microsoft.com/en-us/services/app-service/?v=18.51
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
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.
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.
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.
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
Pros of IndexedDB
Pros of InfluxDB
- Time-series data analysis58
- Easy setup, no dependencies30
- Fast, scalable & open source24
- Open source21
- Real-time analytics20
- Continuous Query support6
- Easy Query Language5
- HTTP API4
- Out-of-the-box, automatic Retention Policy4
- Offers Enterprise version1
- Free Open Source version1
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Cons of IndexedDB
Cons of InfluxDB
- Instability4
- Proprietary query language1
- HA or Clustering is only in paid version1
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