> For the complete documentation index, see [llms.txt](https://upsolver.gitbook.io/content/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://upsolver.gitbook.io/content/resources/blog.md). # Blog ## Upsolver News * [Upsolver Announces Support for Polaris Catalog](https://www.upsolver.com/blog/support-polaris-catalog?utm_source=documentation\&utm_medium=comunity_pages\&utm_campaign=blogs) * [Upsolver Announces Iceberg Table Mirroring to Snowflake](https://www.upsolver.com/blog/upsolver-announces-iceberg-table-mirroring-to-snowflake) * [Deliver Data to ClickHouse Cloud 100x Faster with Upsolver](https://www.upsolver.com/blog/deliver-data-to-clickhouse-cloud-100x-faster-with-upsolver) * [Upsolver Named Data Movement Partner by PuppyGraph](https://www.upsolver.com/blog/upsolver-named-data-movement-partner-by-puppygraph) * [Upsolver Announces Zero-ETL and lakehouse Optimization for Apache Iceberg](https://www.upsolver.com/blog/upsolver-announces-zero-etl-and-lakehouse-optimization-for-apache-iceberg) * [Data Ingestion Solutions Review: 11 Key Takeaways](https://www.upsolver.com/blog/data-ingestion-solutions-review-11-key-takeaways) * [Announcing: Upsolver joins the Connect with Confluent (CwC) Program](https://www.upsolver.com/blog/announcing-upsolver-joins-the-connect-with-confluent-cwc-program) * [A Scalable Way to Deliver NoSQL Prod Data to Analytics Environments](https://www.upsolver.com/blog/a-scalable-way-to-replicate-your-mongodb-data) * [Upsolver Announces Support for AWS for Advertising and Marketing Initiative](https://www.upsolver.com/blog/upsolver-announces-support-for-aws-for-advertising-and-marketing-initiative) ## Data Lakes & Lakehouses * [Simplifying Iceberg Table Partitioning Using Adaptive Clustering](https://www.upsolver.com/blog/iceberg-adaptive-clustering) * [Effortless Table Management with Adaptive Optimizer for Iceberg: Boost Performance & Cut Costs](https://www.upsolver.com/blog/adaptive-optimizer-iceberg?utm_source=documentation\&utm_medium=comunity_pages\&utm_campaign=blogs) * [Simplifying Iceberg Table Partitioning Using Adaptive Clustering](https://www.upsolver.com/blog/iceberg-adaptive-clustering?utm_source=documentation\&utm_medium=comunity_pages\&utm_campaign=blogs) * [An Introduction to Polaris Catalog for Apache Iceberg](https://www.upsolver.com/blog/polaris-catalog-apache-iceberg?utm_source=documentation\&utm_medium=comunity_pages\&utm_campaign=blogs) * [Optimizing Your Data Lakehouse for Cost Efficiency](https://www.upsolver.com/blog/optimizing-your-apache-iceberg-lakehouse-for-cost-efficiency) * [Iceberg Performance Benchmarks: Tabular, Snowflake, AWS Glue and Upsolver Compared](https://www.upsolver.com/blog/iceberg-performance-benchmark) * [The Iceberg Data Lakehouse Stack: Choose the Right Building Blocks](https://www.upsolver.com/blog/iceberg-lakehouse-stack-tools) * [Cut Data Warehouse Costs in Half with Apache Iceberg](https://www.upsolver.com/blog/cut-data-warehouse-costs-in-half-with-apache-iceberg) * [Iceberg 101: A Guide to Iceberg Partitioning](https://www.upsolver.com/blog/iceberg-partitioning) * [Iceberg 101: Ten Tips to Optimize Performance](https://www.upsolver.com/blog/optimize-iceberg-performance) * [Iceberg 101: Working with Iceberg Tables](https://www.upsolver.com/blog/iceberg-tables) * [Iceberg 101: Better Data Lakes with Apache Iceberg](https://www.upsolver.com/blog/iceberg-data-lake) * [Iceberg 101: What is the Iceberg Table Format?](https://www.upsolver.com/blog/iceberg-101-what-is-the-iceberg-table-format) * [An Introduction to the Data Lakehouse for Data Warehouse Users](https://www.upsolver.com/blog/data-lakehouse-warehouse) * [Ingesting Operational Data into an Analytics Lakehouse on Iceberg](ps://www.upsolver.com/blog/ingesting-operational-data-into-an-analytics-lakehouse-on-iceberg) * [Iceberg Architecture Examples: How Iceberg Powers Data and ML Applications at Adobe, Netflix, LinkedIn, Salesforce, and Airbnb](https://www.upsolver.com/blog/iceberg-architecture-examples) * [Lakehouse vs. Data Lake: The Ultimate Guide](https://www.upsolver.com/blog/lakehouse-vs-data-lake-the-ultimate-guide) * [How Apache Iceberg is Reshaping Data Lake File Management ](https://www.upsolver.com/blog/apache-iceberg-tables) * [Apache Iceberg vs Parquet – File Formats vs Table Formats](https://www.upsolver.com/blog/apache-iceberg-vs-parquet-file-formats-vs-table-formats) * [Moving data from a lake to Snowflake](https://www.upsolver.com/blog/moving-data-from-a-lake-to-snowflake) * [Migrating a Self-Managed Data Lake to Snowflake](https://www.upsolver.com/blog/migrating-a-self-managed-data-lake-to-snowflake) * [Why we built a SQL-based solution to unify batch and stream workflows](https://www.upsolver.com/blog/why-we-built-a-sql-based-solution-to-unify-batch-and-stream-workflows) ## Streaming Data * [Adapting Iceberg for High-Scale Streaming Data](https://www.upsolver.com/blog/adapting-iceberg-for-high-scale-streaming-data) * [Snowpipe Streaming: What’s New, Use Cases, and Best Practices](https://www.upsolver.com/blog/snowpipe-streaming) * [Common Challenges with Apache Airflow and How to Address Them](https://www.upsolver.com/blog/common-challenges-with-apache-airflow-and-how-to-address-them) * [Apache Kafka Use Cases: When To Use It? When Not To?](https://www.upsolver.com/blog/apache-kafka-use-cases-when-to-use-not) ## Cloud Architecture * [Getting Started with Apache Iceberg on Amazon S3](https://www.upsolver.com/blog/getting-started-with-apache-iceberg-on-amazon-s3) * [Effortless Table Management with Adaptive Optimizer for Apache Iceberg: Boost Performance & Cut Costs](https://www.upsolver.com/blog/adaptive-optimizer-iceberg) * [Optimizing Data Storage and Querying with Trino, MinIO, and Apache Iceberg](https://www.upsolver.com/blog/trino-minio-iceberg) * [Comparing the Top Iceberg Ingestion Tools - Upsolver, ELT, Open Source](https://www.upsolver.com/blog/comparing-the-top-iceberg-ingestion-tools-upsolver-elt-open-source) * [VPC Flow Log Analytics with PuppyGraph and Upsolver](https://www.upsolver.com/blog/vpc-flow-log-analytics) * [Snowflake Data Ingestion Strategies Decoded: A Guided Tour for Data Engineers](https://www.upsolver.com/blog/snowflake-ingestion) * [What is the Parquet File Format? Use Cases & Benefits](https://www.upsolver.com/blog/apache-parquet-why-use) ## Use Cases * [Introducing Automated Ingestion for dbt Core](https://www.upsolver.com/blog/introducing-automated-ingestion-for-dbt-core) * [How SQLake Auto-Orchestrates Your Pipelines](https://www.upsolver.com/blog/how-sqlake-auto-orchestrates-your-pipelines) * [How to publish data to another AWS account’s catalog](https://www.upsolver.com/blog/how-to-publish-data-to-another-aws-accounts-catalog) * [Analyzing Amazon VPC Flow Logs Using SQL](https://www.upsolver.com/blog/analyzing-amazon-vpc-flow-logs-using-sql) ## Building Data Pipelines * [24 Features to Boost Your Data Movement in 2024: Part 2](https://www.upsolver.com/blog/24-features-to-boost-your-data-movement-in-2024-part-2) * [24 Features to Boost Your Data Movement in 2024: Part 1](https://www.upsolver.com/blog/24-features-to-boost-your-data-movement-in-2024-part-1) * [The 5 Pillars of Data Observability](https://www.upsolver.com/blog/the-5-pillars-of-data-observability) * [Fivetran MAR Pricing vs Upsolver Volume Pricing](https://www.upsolver.com/blog/fivetran-pricing) * [6 Popular CDC Tools Compared (July 2023 Edition)](https://www.upsolver.com/blog/cdc-tools-comparison-guide) * [Airbyte vs Fivetran vs Upsolver – Which is the Best CDC Tool?](https://www.upsolver.com/blog/airbyte-vs-fivetran) * [Achieving Upserts with Snowpipe in Snowflake: Strategies and Alternatives](https://www.upsolver.com/blog/snowpipe-upserts) * [What is Big Data Ingestion?](https://www.upsolver.com/blog/what-is-big-data-ingestion) * [Kafka to Snowflake: What’s the Best Ingestion Method?](https://www.upsolver.com/blog/kafka-to-snowflake) * [How to Build Streaming Data Pipelines with Redpanda and Upsolver](https://www.upsolver.com/blog/how-to-build-streaming-data-pipelines-with-redpanda-and-upsolver-sqlake) ## Change Data Capture * [CDC to Iceberg: 4 Major Challenges, and How We Solved Them](https://www.upsolver.com/blog/cdc-to-iceberg-4-major-challenges-and-how-we-solved-them) * [MySQL CDC to Iceberg Lake in Minutes](https://www.upsolver.com/blog/how-to-replicate-mysql-tables-to-your-iceberg-data-lake-using-cdc) * [Debezium vs Maxwell: Detailed Comparison of Open-source CDC Tools](https://www.upsolver.com/blog/debezium-vs-maxwell) * [Snowflake CDC: Basics, Scale Challenges, and Tools](https://www.upsolver.com/blog/snowflake-cdc) * [Debezium for CDC: Benefits and Pitfalls](https://www.upsolver.com/blog/debezium-vs-upsolver) * [4 Steps to Postgres CDC – Replicate Postgres Changes to your Data Lake](https://www.upsolver.com/blog/how-to-replicate-postgresql-tables-to-your-data-lake-using-cdc) * [Understanding Debezium Outbox Pattern](https://www.upsolver.com/blog/understanding-debezium-outbox-pattern) * [How to Build a MySQL CDC Pipeline in Minutes](https://www.upsolver.com/blog/how-to-replicate-mysql-tables-to-your-data-lake-using-cdc) ## Release Notes ### 2024 * [Upsolver August 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-august-2024-feature-summary) * [Upsolver July 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-july-2024-feature-summary) * [Upsolver June 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-june-2024-feature-summary) * [Upsolver May 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-may-2024-feature-summary) * [Upsolver April 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-april-2024-feature-summary) * [Upsolver March 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-march-2024-feature-summary) * [Upsolver February 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-february-2024-feature-summary) * [Upsolver January 2024 Feature Summary](https://www.upsolver.com/blog/upsolver-january-2024-feature-summary) {% hint style="success" %} **Want More?** Check out the [blog](https://www.upsolver.com/blog) page on our website for more articles. If there's a topic we haven't included that you'd like us to cover, please [let us know](https://www.upsolver.com/contact). {% endhint %} --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://upsolver.gitbook.io/content/resources/blog.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.