Airtable
Asana
Trello
Microsoft Teams
Creativity 365
Basecamp
RingCentral Video
Wrike
Apache Flink
Apache Spark
Amazon Kinesis
Spring Framework
Spark Mail
Apache Airflow
Confluent
Grails
Airtable Apache FlinkAirtable is a powerful cloud-based software that combines spreadsheets and databases, offering real-time collaboration and customizable features for efficient task management1.
Based on our record, Airtable should be more popular than Apache Flink. It has been mentiond 129 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
For the backend, I opted for Airtable as a database. It's a simple, no-code solution that I've used before. It's not the most powerful database, but it's perfect for a project like this. I could easily add, edit, and delete records, and it has an embeddable form functionality that I used for user submissions. - Source: dev.to / 3 months ago
Airtable.com — Looks like a spreadsheet, but it's a relational database unlimited bases, 1,200 rows/base, and 1,000 API requests/month. - Source: dev.to / 4 months ago
The ?XXXXX part of the URL identifies the type of interface page it is. Just copy that and then your formula is just "https://airtable.com.../...?XXXXXX=" & RECORD_ID() I'm not sure it works in every type of interface page (where you've started from a blank page for example). There has to be something to identify the record viewed from the page, if you see what I mean. Source: 10 months ago
So I started building something on airtable.com that would allow me to easily track updates for each batch. What in your experience would make sense to track that I may be missing? Source: 10 months ago
For character sheets, timelines and having records of chapters and scenes, I really really love Airtable. I have some examples here. Source: 12 months ago
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 / 2 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 / 22 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
Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Microsoft Teams - Microsoft Teams provides the enterprise-level security, compliance and management features you expect from Office 365, including broad support for compliance standards, and eDiscovery and legal hold for channels, chats, and files.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.
