Haystack Analytics
LinearB
GitPrime
Waydev
Swarmia
CodeClimate
Athenian
Teamplify
Amazon Redshift
Google BigQuery
Microsoft SQL Server
Microsoft Office Access
Brilliant Database
Firebird
Microsoft SQL Server Compact
CompactView
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 Amazon RedshiftHaystack Analytics's answer
Engineering Leaders and Managers
Based on our record, Amazon Redshift seems to be a lot more popular than Haystack Analytics. While we know about 30 links to Amazon Redshift, 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
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 / 6 months ago
If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, youโve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming โ one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / over 1 year ago
Postgres can be easily adapted to build highly tailored solutions. For instance, Amazon Redshift can be considered a highly scalable fork of Postgres. Itโs a distributed database focusing on OLAP workloads that you can deploy in AWS. - Source: dev.to / over 1 year ago
With the transition from ETL to ELT, data warehouses have ascended to the role of data custodians, centralizing customer data collected from fragmented systems. This pivotal shift has been enabled by a suite of powerful tools: Fivetran and Airbyte streamline the extraction and loading, DBT handles the transformation, and robust warehousing solutions like Snowflake and Redshift store the data. While traditionally... - Source: dev.to / almost 2 years ago
They differ from conventional analytic databases like Snowflake, Redshift, BigQuery, and Oracle in several ways. Conventional databases are batch-oriented, loading data in defined windows like hourly, daily, weekly, and so on. While loading data, conventional databases lock the tables, making the newly loaded data unavailable until the batch load is fully completed. Streaming databases continuously receive new... - Source: dev.to / over 2 years 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.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
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.
Microsoft SQL Server - Microsoft Azure is an open, flexible, enterprise-grade cloud computing platform. Move faster, do more, and save money with IaaS + PaaS. Try for FREE.
Waydev - Waydev analyzes your codebase from Github, Gitlab, Azure DevOps & Bitbucket to help you bring out the best in your engineers work.
Microsoft Office Access - Access is now much more than a way to create desktop databases. Itโs an easy-to-use tool for quickly creating browser-based database applications.
