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PipelineDB

7
18
+ 1
0
TimescaleDB

158
268
+ 1
41
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PipelineDB vs TimescaleDB: What are the differences?

Developers describe PipelineDB as "The Streaming SQL Database". PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables. 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.

PipelineDB can be classified as a tool in the "Database Tools" category, while TimescaleDB is grouped under "Databases".

TimescaleDB is an open source tool with 7.28K GitHub stars and 385 GitHub forks. Here's a link to TimescaleDB's open source repository on GitHub.

Advice on PipelineDB and TimescaleDB
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TimescaleDBTimescaleDBMongoDBMongoDB
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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 · 78.5K 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 PipelineDB and TimescaleDB
Benoit Larroque
Principal Engineer at Sqreen · | 2 upvotes · 55.7K 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 PipelineDB
Pros of TimescaleDB
    Be the first to leave a pro
    • 8
      Open source
    • 7
      Easy Query Language
    • 6
      Time-series data analysis
    • 5
      Established postgresql API and support
    • 4
      Reliable
    • 2
      Paid support for automatic Retention Policy
    • 2
      Fast and scalable
    • 2
      Chunk-based compression
    • 2
      Postgres integration
    • 2
      High-performance
    • 1
      Case studies

    Sign up to add or upvote prosMake informed product decisions

    Cons of PipelineDB
    Cons of TimescaleDB
      Be the first to leave a con
      • 3
        Licensing issues when running on managed databases

      Sign up to add or upvote consMake informed product decisions

      - No public GitHub repository available -

      What is PipelineDB?

      PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.

      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.

      Need advice about which tool to choose?Ask the StackShare community!

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

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      What are some alternatives to PipelineDB and TimescaleDB?
      Apache Spark
      Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
      RethinkDB
      RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
      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.
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      KSQL
      KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.
      See all alternatives