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dbt

500
451
+ 1
15
Redis

59.9K
45.9K
+ 1
3.9K
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Pros of dbt
Pros of Redis
  • 5
    Easy for SQL programmers to learn
  • 2
    CI/CD
  • 2
    Schedule Jobs
  • 2
    Reusable Macro
  • 2
    Faster Integrated Testing
  • 2
    Modularity, portability, CI/CD, and documentation
  • 887
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 165
    Stable
  • 156
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 23
    Pub/Sub
  • 22
    Great community
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    Lists
  • 10
    NoSQL
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 8
    Bitmaps
  • 7
    Open Source
  • 7
    Keys with a limited time-to-live
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Runs server side LUA
  • 4
    Transactions
  • 4
    Networked
  • 4
    Outstanding performance
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    LRU eviction of keys
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Temporarily kept on disk
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Scalable
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Existing Laravel Integration
  • 2
    Simple

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Cons of dbt
Cons of Redis
  • 1
    Only limited to SQL
  • 1
    Cant do complex iterations , list comprehensions etc .
  • 1
    People will have have only sql skill set at the end
  • 1
    Very bad for people from learning perspective
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL

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What is dbt?

dbt is a transformation workflow that lets teams deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.

What is Redis?

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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What companies use dbt?
What companies use Redis?
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What tools integrate with dbt?
What tools integrate with Redis?

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What are some alternatives to dbt and Redis?
act
Rather than having to commit/push every time you want test out the changes you are making to your .github/workflows/ files (or for any changes to embedded GitHub actions), you can use this tool to run the actions locally. The environment variables and filesystem are all configured to match what GitHub provides.
Airflow
Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
Looker
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.
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.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
See all alternatives