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 / 10 days 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 / 30 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

It goes beyond just joining postgres to hubspot and stripe even when humans are doing it. Typos in source systems, duplicative data, unwarranted prefixes, suffixes, stuff you don't care about, columns named c0,c1,c2 etc. A semantic layer is just really all about defining data models in the domain of interest. It's the hardest part in dealing with data strategies, very manual, very company and process and history... - Source: Hacker News / 3 months ago

Shameless plug on https://syncari.com. I'm a founder and this is part of our thesis as. A single data, control and analytics plane for all systems (CRM, internal systems, marketing, support, product usage and billing). - Source: Hacker News / 3 months ago

Data extraction tools can be a valuable asset for businesses that need data integration and extraction from online sources. By following the steps outlined above, you can use these tools to efficiently and accurately redact and integrate your online data. - Source: dev.to / over 1 year ago