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Product
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April 1, 2025
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e6data Team
e6data with Microsoft Fabric: Faster Queries, Lower Bills—Without Leaving OneLake
e6data Team
April 1, 2025
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March 31, 2025
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e6data Team
e6data for MS Fabric: 33% Increase in Performance and Optimized Capacity
e6data Team
March 31, 2025
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Engineering
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March 27, 2025
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Karthic Rao
Stateful vs Stateless Stream Processing: Watermarks, Barriers, and Performance Trade-offs
Karthic Rao
March 27, 2025
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Engineering
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March 19, 2025
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Karthic Rao
Scaling Iceberg Writes with Confidence: A Conflict-Free Distributed Architecture for Fast, Concurrent, Consistent Append-Only Writes
Karthic Rao
March 19, 2025
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Engineering
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March 17, 2025
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Karthic Rao
Snappy Vs. ZSTD in Apache Iceberg: A Debate on Fast Writes Amid Small-File Challenges
Karthic Rao
March 17, 2025
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News
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March 11, 2025
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e6data Team
e6data Achieves SOC 2, HIPAA, GDPR, and ISO 27001, Reinforcing Its Enterprise-grade Security and Zero-Migration Architecture
e6data Team
March 11, 2025
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Engineering
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January 3, 2025
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Karthic Rao
Under the Hood of Apache Iceberg: An Inside Look at the Metadata Evolution After Compaction
Karthic Rao
January 3, 2025
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Engineering
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November 5, 2024
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Sweta Singh
The Shuffle Series: Part 1: Understanding the Shuffle Problem in Distributed Computing
Sweta Singh
November 5, 2024
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Engineering
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November 12, 2024
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Vishnu Vasanth
The Lakehouse Evolution: Making Object Storage the Backbone of Modern Analytics
Vishnu Vasanth
November 12, 2024

Time Series

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Engineering
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March 23, 2026
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Samyak Sarnayak
The Lock Nobody Held: Deadlocking a Tokio Mutex Without Holding a Lock
Samyak Sarnayak
March 23, 2026
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Engineering
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October 16, 2025
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Arnav Borkar
Metadata at Scale: Tackling Apache Iceberg Tables with Tens of Millions of Files
Arnav Borkar
October 16, 2025
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Engineering
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October 10, 2025
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Samyak Sarnayak
Faster JSON in SQL: A Deep Dive into Variant Data Type
Samyak Sarnayak
October 10, 2025
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Engineering
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September 19, 2025
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Yash Bhisikar
German Strings: The 16-Byte Secret to Faster Analytics
Yash Bhisikar
September 19, 2025
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Engineering
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September 12, 2025
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Rajath Gowda
Partition Projection in the Data Lakehouse: Cheaper Pipelines, Faster Queries
Rajath Gowda
September 12, 2025
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Engineering
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August 8, 2025
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Adishesh Kishore
Embedding Essentials: From Cosine Similarity to SQL with Vectors
Adishesh Kishore
August 8, 2025
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Product
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August 5, 2025
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e6data Team
e6data’s Hybrid Data Lakehouse: 10x Faster Queries, Near-Zero Egress, Sub-Second Latency
e6data Team
August 5, 2025
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Engineering
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Cost
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July 25, 2025
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Rajath Gowda
Building a Modern Data Pipeline in Snowflake: From Snowpipe to Managed Iceberg Tables with Sync Checks
Rajath Gowda
July 25, 2025
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Product
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July 24, 2025
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e6data Team
Improved open-table analytics stack with Iceberg, Polaris, Hudi, Delta Lake
e6data Team
July 24, 2025