Haystack Analytics
LinearB
GitPrime
Waydev
Swarmia
CodeClimate
Athenian
Teamplify
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Amazon EMR
Google Cloud Dataflow
Rakam
Haystack is a real-time delivery analytics platform designed for engineering leaders like CTOs, VPs of Engineering, Directors of Software Engineering, and Engineering Managers. Haystack provides actionable insights that enable data-driven decision-making, aligning engineering performance with business objectives. Haystack platform integrates seamlessly with essential developer tools like GitHub and JIRA, offering a comprehensive view of team productivity and delivery efficiency.
Leading companies like AngelList, Shutterstock, Schneider Electric, and many more trust Haystack to optimize their development processes. By transforming historical Git data into objective insights, we help you identify bottlenecks and visualize trends, ensuring timely project delivery and sustained business growth. Our analytics dashboard allows you to monitor critical metrics such as cycle time, making it easier to spot inefficiencies before they escalate into costly delays.
Haystack helps engineering leaders to mitigate risks and improve workflow efficiency. With a unified view of the entire delivery lifecycle, you can track KPIs, compare performance trends, and make informed decisions that drive measurable outcomes. Our platform goes beyond merely measuring productivity; it equips you with the tools to foster continuous improvement and innovation within your teams.
Designed to scale with your organization, Haystack is the competitive advantage that data-driven engineering teams need to thrive. By leveraging analytics, you can transform your engineering operations, enhance collaboration, and accelerate your path to market success. Join top companies in harnessing the power of Haystack for a more efficient and effective engineering process.
Haystack Analytics Google BigQueryHaystack Analytics's answer
Engineering Leaders and Managers
Based on our record, Google BigQuery seems to be a lot more popular than Haystack Analytics. While we know about 47 links to Google BigQuery, we've tracked only 2 mentions of Haystack Analytics. 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.
Heads up: site is not loading. Ios Safari & macOS Chrome. Mixed Content: The page at 'https://usehaystack.io/' was loaded over HTTPS, but requested an insecure favicon 'http://www.usehaystack.io/favicon.ico'. This request has been blocked; the content must be served over HTTPS. - Source: Hacker News / over 5 years ago
Hey HN! I'm Julian, co-founder of Haystack (https://usehaystack.io). Weโre building one-click dashboards and alerts using Github data. While managing teams from startups to more established companies like Cloudflare, my cofounder Kan and I were constantly trying to improve our team and process. But it was pretty tough to tell if our efforts were paying off. Even tougher to tell where we could improve. We tried... - Source: Hacker News / over 5 years ago
We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 3 months ago
Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 4 months ago
Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 5 months ago
SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโwhile dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 7 months ago
Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 8 months ago
LinearB - LinearB delivers software leaders the insights they need to make their engineering teams better through a real-time SaaS platform. Visibility into key metrics paired with automated improvement actions enables software leaders to deliver more.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.โWhat is Apache Spark?
GitPrime - GitPrime uses data from any Git based code repository to give management the software engineering metrics needed to move faster and optimize work patterns.
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
