
GitLab
GitHub
BitBucket
CircleCI
Jira
Jenkins
Gitea
SourceForge
Apache Parquet
Apache Spark
Apache Arrow
Amazon S3
DuckDB
Apache Avro
Apache Kafka
Hugging Face
GitLab
Apache ParquetGitLab is well-suited for developers, DevOps engineers, project managers, and teams that require robust CI/CD capabilities, strong security features, and an open-source platform that can be self-hosted or used as a cloud service. It is particularly beneficial for organizations looking for a comprehensive solution to streamline their development workflows.
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Based on our record, GitLab should be more popular than Apache Parquet. It has been mentiond 144 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.
We use GitHub here as an example, but there are also other hosts you could explore like GitLab and BitBucket. - Source: dev.to / 4 months ago
Expertise. The SaaS provider is declaring: "I am good at XYZ; I can deliver it better than any of my competitors, and I constantly work to improve how I deliver it." Who do you think can better run GitLab, your already overworked Operations team, or GitLab itself? - Source: dev.to / 5 months ago
Integration Capabilities: How easily does it plug into your daily workflow? Look for deep integrations with your IDE, source control (like GitHub or GitLab), and especially your CI/CD pipeline. - Source: dev.to / 6 months ago
Connect your GitLab account for seamless version control. - Source: dev.to / 8 months ago
Web Check CI stands out because it is the first CI/CD module of its kind available for GitLab! It's built on Google's Baseline initiative, the new standard for web platform compatibility. Instead of guessing which features are safe to use, developers get authoritative answers based on real browser support data. - Source: dev.to / 11 months ago
Apache Iceberg fits these requirements well. Iceberg stores data as immutable Apache Parquet files and adds them through atomic commits, so readers always see a consistent snapshot. A separate metadata layer prunes files by their statistics before the data itself is ever read, and those statistics can be extended to match an observability filtering profile. - Source: dev.to / 2 months ago
Depends on the domain. There's a bunch of sciences using large datasets served up efficiently using static file formats, e.g., https://zarr.dev/ and https://parquet.apache.org/. - Source: Hacker News / 3 months ago
The data files themselves are still standard Parquet or ORC. The table format adds a metadata layer on top that gives those files the properties of a database table. - Source: dev.to / 4 months ago
The dataset is huge - in parquet conversion - it is total 9gb. And in raw PNG image nested folders - it is 67 gigabytes. Huge... - Source: dev.to / 6 months ago
The solution is to standardize on columnar formats like Apache Parquet. Parquet stores data in columns, not rows, which immediately enables column pruning. If a query is SELECT avg(price) FROM sales, the engine reads only the price column and ignores all others. This can reduce storage footprints by up to 75% compared to raw formats and is a cornerstone of modern analytics performance. - Source: dev.to / 10 months ago
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Apache Arrow - Apache Arrow is a cross-language development platform for in-memory data.
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.