Apache Flink Reviews

tray.io Reviews

Apache Flink mentions (30)

• Show HN: Restate, low-latency durable workflows for JavaScript/Java, in Rust

  Restate is built as a sharded replicated state machine similar to how TiKV (https://tikv.org/), Kudu (https://kudu.apache.org/kudu.pdf) or CockroachDB (https://github.com/cockroachdb/cockroach) since it makes it possible to tune the system more easily for different deployment scenarios (on-prem, cloud, cost-effective blob storage). Moreover, it allows for some other cool things like seamlessly moving from one log... - Source: Hacker News / 3 days ago

• Array Expansion in Flink SQL

  I’ve recently started my journey with Apache Flink. As I learn certain concepts, I’d like to share them. One such "learning" is the expansion of array type columns in Flink SQL. Having used ksqlDB in a previous life, I was looking for functionality similar to the EXPLODE function to "flatten" a collection type column into a row per element of the collection. Because Flink SQL is ANSI compliant, it’s no surprise... - Source: dev.to / 23 days ago

• Show HN: An SQS Alternative on Postgres

  You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / about 1 month ago

• Top 10 Common Data Engineers and Scientists Pain Points in 2024

  Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 2 months ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 4 months ago

tray.io mentions (15)

• How do you integrate your Shopify store with third-party tools and services?

  Use Integration Platforms: Tools like Zapier, Integromat, and Unified, AI-powered iPaaS for every team to automate at scale | Tray.io let you connect Shopify with other apps without coding. Source: 8 months ago

• Reverse ETL recommendations?

  Check out tray.io - it's basically "more technical Zapier". Source: 12 months ago

• Cashflow forecast based on client average days to pay

  Anaplan (anaplan.com) is an option as you'll need to setup an integration via tray.io. They are not add-ons but separate applications that will take your Xero data and replicate a copy of the data into Anaplan. Once the Xero data is in Anaplan you'll be able to do the detailed Cash Flow. I don't work for any of the companies discussed here. Source: over 1 year ago

• Project management

  Check out tray.io they have connectors with Monday.com and Atera which can do alot of the heavy lifting. All you would need to do is create rules. Use Monday.com to house the information tied to the Atera Customer or Device. Source: over 1 year ago

• Airtable Extension for Web Scraping

  The best way to do something like this would be to implement a tray.io, but I'd like to know if there's an extension or addon that can also tackle this workflow. Source: over 1 year ago