The first
AI co-pilot built for Apache
Spark
DataFlint clears the path for your data team at every stage of the big data lifecycle by providing a production-aware AI Co-pilot for Apache spark — so they can 10x their velocity and impact.DataFlint transforms every team member into a big data expert
“Amazing product!—we`re using it widely at Wix”
“We`re deploying the new version...”
“That`s great news! This is such a great replacement for the Spark UI. Seamless to setup and packed with data that actually makes sense.”
“Great news! When you have a hunch about the performance of your spark job, it is great that DataFlint backs your hunch with all the metrics and alerts. Much more easier to pinpoint room for inprovements with DataFlint now!”
“Will start experimenting with the new version ASAP.”
“Super helpful for our DE team 💪🏻”
“DataFlint is a must-have if you are running Apache Spark!”
“DataFlint has been a game changer in Spark observability for Intel Granulate and I`m glad to see it`s the case for Amazon Web Services (AWS) as well”
“great job Meni Shmueli and Daniel A. ! Proactively monitoring spark metrics to derive actionable insights is super important and often overlooked ”
When data engineers
get unblocked...
cutting
runtime and costs 100XA data analyst at Similarweb developed a critical pipeline that broke down in production. It was running out of memory and showing complicated error messages that were hard to understand.
velocity and impact.
Product FAQ’s
DataFlint offers several key benefits:
- Faster Issue Resolution: Instantly performs root cause analysis for failing Spark pipelines.
- Optimized Performance: Provides code suggestions to optimize join strategies, resource allocation, and more, leading to significantly faster execution times (e.g., 13x faster in our Similarweb case study).
- Reduced Costs: Helps cut infrastructure costs dramatically by identifying inefficiencies (e.g., 100x cost reduction in the case study).
- Increased Team Velocity: Empowers your data team to ship data pipelines faster and more reliably, boosting overall velocity and impact (aiming for 10x improvement).
- Enhanced Observability: Offers a control center for immediate visibility into failing jobs, performance bottlenecks, and cost metrics.
DataFlint is designed for broad compatibility. It integrates with:
- Spark Platforms: k8s, standalone Spark, EMR, Databricks.
- Storage: S3, Azure Blob Storage, Hadoop HDFS, Google object storage.
- Orchestration: Airflow, Databricks Jobs.
- IDEs & Tools: VScode, Cursor, IntelliJ for code suggestions.
- Observability: DataFlint Provides a SaaS UI dashboard and integrates with Slack and Managed Spark History Server.
DataFlint prioritizes your data security and privacy. We monitor and analyze Spark logs, which are performance logs detailing job execution metrics and system events, not your underlying business data. This focus on operational metadata means there are minimal privacy concerns related to sensitive information. Furthermore, DataFlint is AICPA SOC 2 compliant, demonstrating our commitment to robust security controls and practices.