- Aerospike
- Akamas
- AlloyDB
- ApertureDB
- Arrow
- Berkeley DB
- BlazingDB
- Brytlyt
- Chaos Mesh
- Citus
- CockroachDB
- Convex
- CrateDB
- Databricks
- Datometry
- dbt
- Delta Lake
- Dremio
- DSQL
- DVMS
- EraDB
- eXtremeDB
- Fauna
- Featureform
- Firebolt
- Fluss
- Gaia
- GlareDB
- GoogleSQL
- GreptimeDB
- Heron
- Iceberg
- InfluxDB
- kdb
- ksqlDB
- LeanStore
- LMDB
- MapD
- Materialize
- Milvus
- MonetDB
- Mooncake
- MySQL
- Neon
- Noria
- OceanBase
- Oracle
- OxQL
- Pinecone
- PlanetScale
- PostgresML
- PRQL
- QMDB
- QuestDB
- Redshift
- RisingWave
- Rockset
- rqlite
- Samza
- SingleStore
- SLOG
- Snowflake
- SpiceDB
- SplinterDB
- SQL Server
- SQLite
- Stardog
- Striim
- Swarm64
- Technical University of Munich
- TiDB
- TileDB
- Tokutek
- Umbra
- Vertica
- VoltDB
- Weaviate
- XTDB
- YugabyteDB
- AirFlow
- Alibaba
- Anna
- APOLLO
- Azure Cosmos DB
- BigQuery
- Bodo
- Cassandra
- Chroma
- ClickHouse
- Confluent
- CouchDB
- CrocodileDB
- DataFusion
- Datomic
- Debezium
- Dolt
- Druid
- DuckDB
- EdgeDB
- Exon
- FASTER
- FeatureBase
- Feldera
- Fluree
- FoundationDB
- Gel
- Google Spanner
- Greenplum
- HarperDB
- Hudi
- Impala
- Jepsen
- Kinetica
- LanceDB
- Litestream
- Malloy
- MariaDB
- MemSQL
- Modin
- MongoDB
- MotherDuck
- Napa
- NoisePage
- NuoDB
- OpenDAL
- OtterTune
- ParadeDB
- Pinot
- Polaris
- PostgreSQL
- Qdrant
- QuasarDB
- RavenDB
- RelationalAI
- RocksDB
- RonDB
- SalesForce
- ScyllaDB
- sled
- Smooth
- Spice.ai
- Splice Machine
- SQL Anywhere
- SQLancer
- SQream
- StarRocks
- Summingbird
- Synnada
- TerminusDB
- TigerBeetle
- TimescaleDB
- Trino
- Velox
- Vitesse
- Vortex
- WiredTiger
- Yellowbrick
- Aerospike
- Alibaba
- ApertureDB
- Azure Cosmos DB
- BlazingDB
- Cassandra
- Citus
- Confluent
- CrateDB
- DataFusion
- dbt
- Dolt
- DSQL
- EdgeDB
- eXtremeDB
- FeatureBase
- Firebolt
- FoundationDB
- GlareDB
- Greenplum
- Heron
- Impala
- kdb
- LanceDB
- LMDB
- MariaDB
- Milvus
- MongoDB
- MySQL
- NoisePage
- OceanBase
- OtterTune
- Pinecone
- Polaris
- PRQL
- QuasarDB
- Redshift
- RocksDB
- rqlite
- ScyllaDB
- SLOG
- Spice.ai
- SplinterDB
- SQLancer
- Stardog
- Summingbird
- Technical University of Munich
- TigerBeetle
- Tokutek
- Velox
- VoltDB
- WiredTiger
- YugabyteDB
- AirFlow
- AlloyDB
- APOLLO
- Berkeley DB
- Bodo
- Chaos Mesh
- ClickHouse
- Convex
- CrocodileDB
- Datometry
- Debezium
- Dremio
- DuckDB
- EraDB
- FASTER
- Featureform
- Fluree
- Gaia
- Google Spanner
- GreptimeDB
- Hudi
- InfluxDB
- Kinetica
- LeanStore
- Malloy
- Materialize
- Modin
- Mooncake
- Napa
- Noria
- OpenDAL
- OxQL
- Pinot
- PostgresML
- Qdrant
- QuestDB
- RelationalAI
- Rockset
- SalesForce
- SingleStore
- Smooth
- SpiceDB
- SQL Anywhere
- SQLite
- StarRocks
- Swarm64
- TerminusDB
- TileDB
- Trino
- Vertica
- Vortex
- XTDB
- Akamas
- Anna
- Arrow
- BigQuery
- Brytlyt
- Chroma
- CockroachDB
- CouchDB
- Databricks
- Datomic
- Delta Lake
- Druid
- DVMS
- Exon
- Fauna
- Feldera
- Fluss
- Gel
- GoogleSQL
- HarperDB
- Iceberg
- Jepsen
- ksqlDB
- Litestream
- MapD
- MemSQL
- MonetDB
- MotherDuck
- Neon
- NuoDB
- Oracle
- ParadeDB
- PlanetScale
- PostgreSQL
- QMDB
- RavenDB
- RisingWave
- RonDB
- Samza
- sled
- Snowflake
- Splice Machine
- SQL Server
- SQream
- Striim
- Synnada
- TiDB
- TimescaleDB
- Umbra
- Vitesse
- Weaviate
- Yellowbrick
- Aerospike
- AlloyDB
- Arrow
- BlazingDB
- Chaos Mesh
- CockroachDB
- CrateDB
- Datometry
- Delta Lake
- DSQL
- EraDB
- Fauna
- Firebolt
- Gaia
- GoogleSQL
- Heron
- InfluxDB
- ksqlDB
- LMDB
- Materialize
- MonetDB
- MySQL
- Noria
- Oracle
- Pinecone
- PostgresML
- QMDB
- Redshift
- Rockset
- Samza
- SLOG
- SpiceDB
- SQL Server
- Stardog
- Swarm64
- TiDB
- Tokutek
- Vertica
- Weaviate
- YugabyteDB
- AirFlow
- Anna
- Azure Cosmos DB
- Bodo
- Chroma
- Confluent
- CrocodileDB
- Datomic
- Dolt
- DuckDB
- Exon
- FeatureBase
- Fluree
- Gel
- Greenplum
- Hudi
- Jepsen
- LanceDB
- Malloy
- MemSQL
- MongoDB
- Napa
- NuoDB
- OtterTune
- Pinot
- PostgreSQL
- QuasarDB
- RelationalAI
- RonDB
- ScyllaDB
- Smooth
- Splice Machine
- SQLancer
- StarRocks
- Synnada
- TigerBeetle
- Trino
- Vitesse
- WiredTiger
- Akamas
- ApertureDB
- Berkeley DB
- Brytlyt
- Citus
- Convex
- Databricks
- dbt
- Dremio
- DVMS
- eXtremeDB
- Featureform
- Fluss
- GlareDB
- GreptimeDB
- Iceberg
- kdb
- LeanStore
- MapD
- Milvus
- Mooncake
- Neon
- OceanBase
- OxQL
- PlanetScale
- PRQL
- QuestDB
- RisingWave
- rqlite
- SingleStore
- Snowflake
- SplinterDB
- SQLite
- Striim
- Technical University of Munich
- TileDB
- Umbra
- VoltDB
- XTDB
- Alibaba
- APOLLO
- BigQuery
- Cassandra
- ClickHouse
- CouchDB
- DataFusion
- Debezium
- Druid
- EdgeDB
- FASTER
- Feldera
- FoundationDB
- Google Spanner
- HarperDB
- Impala
- Kinetica
- Litestream
- MariaDB
- Modin
- MotherDuck
- NoisePage
- OpenDAL
- ParadeDB
- Polaris
- Qdrant
- RavenDB
- RocksDB
- SalesForce
- sled
- Spice.ai
- SQL Anywhere
- SQream
- Summingbird
- TerminusDB
- TimescaleDB
- Velox
- Vortex
- Yellowbrick
Nov 18
2025
[Fall 2025] Optimizing the Table Scan Operator: I/O Minimization and Runtime Adaptivity
- Speaker:
- Benjamin Owad
- System:
- Snowflake
Table scan is a foundational operator in any analytical database and is often the primary bottleneck for a given query. This talk provides a technical deep dive into optimizations our team has developed for the table scan operator. First, we will discuss I/O reduction techniques, including pruning strategies to avoid reading unnecessary data and storage request coalescing to batch I/O... Read More
Nov 17
2025
Cortex AISQL: A Production SQL Engine for Unstructured Data
- Speaker:
- Anupam Datta
- System:
- Snowflake
Snowflake’s Cortex AISQL is a production SQL engine that integrates native semantic operations directly into SQL. This integration allows users to write declarative queries that combine relational operations with semantic reasoning, enabling them to query both structured and unstructured data effortlessly. However, making semantic operations efficient at production scale poses fundamental challenges. Semantic operations are more expensive than traditional SQL... Read More
Nov 6
2024
Snowflake, and why the Cloud reshaped the analytics industry
- Speaker:
- Dan Sotolongo
- System:
- Snowflake
Snowflake was the first data warehouse designed from scratch to take advantage of Cloud economics. We'll talk about what that means, why it was such a big deal, and how its design differs from the approaches taken by similar systems. Stay until the end for some bonus content on how Snowflake is bringing stream processing into the DBMS. Zoom link:... Read More
Sep 12
2024
[Fall 2024] Advancing Database Performance and Capabilities at Snowflake
- Speakers:
- Dan Sotolongo, Bowei Chen
- System:
- Snowflake
This talk presents recent research and development at Snowflake aimed at pushing the boundaries of database performance and functionality. In the first section, we will introduce a series of optimizations designed to accelerate query execution within Snowflake’s platform. We will discuss the technical challenges associated with developing general-purpose optimizations and balancing performance improvements across a wide range of workloads. The... Read More
Sep 14
2023
[Fall 2023] Snowflake Tech Talk (Bowei Chen)
- Speaker:
- Bowei Chen
- System:
- Snowflake
Snowflake internals tech talk. Read More
Sep 19
2022
[¡Databases! 2022] Snowflake Iceberg Tables, Streaming Ingest, and Unistore! (Ashish Motivala)
- Speakers:
- Nileema Shingte , Tyler Jones, Ashish Motivala
- System:
- Snowflake
- Video:
- YouTube
Why settle for 1 cool db talk when you can get 3? Snowflake is pushing the boundaries of what a unified cloud data platform can do. Today we'll talk about how Snowflake can be combined with open standards like Apache Iceberg, hard tech to stream data into Snowflake and bring transactional and analytical workloads together in a single platform. Apache... Read More
Dec 7
2020
[Fall 2020] A Peek into Snowflake’s Scalable Architecture
- Speakers:
- Martin Hentschel , Max Heimel
- System:
- Snowflake
Snowflake is an analytic data warehouse offered as a fully-managed service in the cloud. It is faster, easier to use, and far more scalable than traditional on-premise data warehouse offerings and is used by thousands of customers around the world. Snowflake's data warehouse is not built on an existing database or "big data" software platform such as Hadoop—it uses a... Read More
Sep 21
2020
Query Optimization at Snowflake
- Speaker:
- Jiaqi Yan
- System:
- Snowflake
- Video:
- YouTube
In this talk, I will give an introduction to Snowflake's query optimizer. I will talk about the main features of Snowflake's optimizer, explain the main philosophy behind the design decisions, and delve into some unique aspects of the implementation. I will also later expand into our infrastructures to facilitate optimizer development and discuss the opportunities and challenges for implementing and... Read More
May 3
2018
Jiaqi Yan (Snowflake Computing)
- Speaker:
- Jiaqi Yan
- System:
- Snowflake
For partitioned tables, maintaining good clustering properties for frequently accessed dimensions is critical for partition pruning performance. Naive methods of clustering maintenance could be expensive, especially when the clustering dimensions are different from the dimensions with which the data is loaded. On the other hand, approximate clustering is cheaper to maintain while still resulting in good pruning performance. In this... Read More