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 / 1 day ago

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 / 21 days ago

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

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

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

Deploying Dart functions to AWS Lambda enables you to utilize them not only within AWS Lambda but also integrate them with services like Amazon API Gateway, allowing you to leverage them in Flutter applications as well. This unified codebase in Dart offers great convenience. - Source: dev.to / about 1 month ago

Moreover, integrating rate limiting can thwart DDoS attacks, and schema validation can prevent malformed requests, ensuring only legitimate and well-formed traffic reaches your serverless functions. Tools like Amazon API Gateway, Azure API Management, and Google Cloud Endpoints offer these capabilities, allowing you to set up custom authorization workflows and request validation rules that align with your security... - Source: dev.to / about 2 months ago

Amazon API Gateway is a fully managed service by Amazon Web Services that provides customers with the capability to create, publish, maintain, monitor, and secure APIs at any scale. API Gateway is using regional endpoints that can be deployed in multi-AWS Regions to enable reduced latency. - Source: dev.to / 2 months ago

Amazon API Gateway receives the message from the WhatsApp webhook (previously authenticated). - Source: dev.to / 3 months ago

This is where we turn to the tried and true Amazon API Gateway and its many integrations. Using API Gateway, we can use services like AWS Lambda or AWS Step Functions to run logic against the payload that we receive. We can also use these integrations to return responses back to the user. - Source: dev.to / 7 months ago