Based on our record, Apache Flink should be more popular than DuckDB. 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.
I have lived through the hype of Big data it was a time of HDFS+HTable I guess and Hapoop etc. One can't go wrong with DuckDB+SQLite+Open/Elasticsearch either with 6 to 8 even 10 TB of data. [0]. https://duckdb.org/. - Source: Hacker News / 23 days ago
More than once, I have been in a situation where I needed to query CloudTrail logs but was working in a customer environment where they weren’t aggregated to a search interface. Another similar situation is when CloudTrail data events are disabled for cost reasons but need to be temporarily turned on for troubleshooting/audit purposes. While the CloudTrail console offers some (very) limited lookups (for management... - Source: dev.to / 30 days ago
DuckDB: An in-process SQL OLAP database management system. While not a traditional OLAP database, DuckDB is designed to execute analytical queries efficiently, making it suitable for analytical workloads within data-intensive applications. - Source: dev.to / 4 months ago
Easiest way to practically use SIMD table scan database is try out DuckDB: https://duckdb.org/. - Source: Hacker News / 4 months ago
Duckdb so we can make OLAP like queries on the data. - Source: dev.to / 7 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 / 7 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 / 27 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
Apache Druid - Fast column-oriented distributed data store
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
OctoSQL - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
MonetDB - Column-store database
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.