Needs advice
on
TimescaleDB
MongoDB
and
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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6 upvotes·63.3K views
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VP R&D at Zira·
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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6 upvotes·1 comment·57.7K views
Oded Arbel
Oded Arbel
·
April 23rd 2020 at 11:10AM

To echo Yaron, don't sell out RDBM systems so fast - with a correctly designed schema, data throughput of a good engine (such as Postgres or MySQL/Maria) can rival the best of the NoSQL branch.

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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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Avatar of Yaron Lavi

Yaron Lavi

VP R&D at Zira