Builderfly is a SaaS-based eCommerce platform specifically designed for small, mid-size retailers and online sellers to solve their problems of limited budget and lack of knowledge to go online. It is a 360 SaaS platform with shipping, payment gateway, social media, & WhatsApp Integration and much more which suffice all needs of an online seller in one place.
Builderfly provides a special consultative approach to building an online store starting from website design, followed by enabling an online presence with social media & online promotions. They also provide professional support in product photography which enhances the appeal of their products and maximises their sales.
Builderfly has implemented WDIFY (We Do It For You) instead of DIY (Do it yourself) platforms at no extra cost. They can rely on the team of experts at Builderfly to go online in less than 7 days. This has successfully helped in removing doubts in the minds of new online sellers about doing everything right and on time.
Based on our record, Apache Flink seems to be more popular. It has been mentiond 30 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.
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 / 5 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 / 25 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
Shopify - Shopify is a powerful ecommerce platform that includes everything you need to create an online store and sell online. Try it free for 14 days.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
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Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.