- Aerospike
- Akamas
- AlloyDB
- ApertureDB
- Arrow
- Azure Cosmos DB
- BigQuery
- Bodo
- Cassandra
- Chroma
- Citus
- CockroachDB
- Convex
- CrateDB
- Daft
- DataFusion
- Datomic
- dbt
- Delta Lake
- Doris
- Druid
- DuckDB
- EdgeDB
- Exon
- FASTER
- FeatureBase
- Feldera
- Floe
- Fluss
- Gaia
- GlareDB
- GoogleSQL
- GreptimeDB
- Heron
- Hudi
- Impala
- Jepsen
- Kinetica
- Lakebase
- LeanStore
- LMDB
- MapD
- Materialize
- Microsoft SQL Server
- Modin
- MongoDB
- MotherDuck
- MySQL
- Neon
- Noria
- OceanBase
- OpenDAL
- OtterTune
- OxQL
- Pinecone
- Pixeltable
- Polaris
- PostgreSQL
- Qdrant
- QuasarDB
- RavenDB
- RelationalAI
- RocksDB
- RonDB
- SalesForce
- ScyllaDB
- SingleStore
- sled
- Smooth
- SpacetimeDB
- SpiceDB
- SplinterDB
- SQL Server
- SQLite
- Stardog
- Striim
- Swarm64
- Technical University of Munich
- TerminusDB
- TigerBeetle
- TimescaleDB
- TonicDB
- Trino
- Turso
- Velox
- VillageSQL
- VoltDB
- Weaviate
- XTDB
- YugabyteDB
- AirFlow
- Alibaba
- Anna
- APOLLO
- Aurora DSQL
- Berkeley DB
- BlazingDB
- Brytlyt
- Chaos Mesh
- Chronon
- ClickHouse
- Confluent
- CouchDB
- CrocodileDB
- Databricks
- Datometry
- DB9
- Debezium
- Dolt
- Dremio
- DSQL
- DVMS
- EraDB
- eXtremeDB
- Fauna
- Featureform
- Firebolt
- Fluree
- FoundationDB
- Gel
- Google Spanner
- Greenplum
- HarperDB
- HorizonDB
- Iceberg
- InfluxDB
- kdb
- ksqlDB
- LanceDB
- Litestream
- Malloy
- MariaDB
- MemSQL
- Milvus
- MonetDB
- Mooncake
- Multigres
- Napa
- NoisePage
- NuoDB
- OneWill
- Oracle
- Oxla
- ParadeDB
- Pinot
- PlanetScale
- PostgresML
- PRQL
- QMDB
- QuestDB
- Redshift
- RisingWave
- Rockset
- rqlite
- Samza
- Sentry
- Sirius
- SLOG
- Snowflake
- Spice.ai
- Splice Machine
- SQL Anywhere
- SQLancer
- SQream
- StarRocks
- Summingbird
- Synnada
- TeraData
- TiDB
- TileDB
- Tokutek
- TopK
- turbopuffer
- Umbra
- Vertica
- Vitesse
- Vortex
- WiredTiger
- Yellowbrick
- Aerospike
- Alibaba
- ApertureDB
- Aurora DSQL
- BigQuery
- Brytlyt
- Chroma
- ClickHouse
- Convex
- CrocodileDB
- DataFusion
- DB9
- Delta Lake
- Dremio
- DuckDB
- EraDB
- FASTER
- Featureform
- Floe
- FoundationDB
- GlareDB
- Greenplum
- Heron
- Iceberg
- Jepsen
- ksqlDB
- LeanStore
- Malloy
- Materialize
- Milvus
- MongoDB
- Multigres
- Neon
- NuoDB
- OpenDAL
- Oxla
- Pinecone
- PlanetScale
- PostgreSQL
- QMDB
- RavenDB
- RisingWave
- RonDB
- Samza
- SingleStore
- SLOG
- SpacetimeDB
- Splice Machine
- SQL Server
- SQream
- Striim
- Synnada
- TerminusDB
- TileDB
- TonicDB
- turbopuffer
- Velox
- Vitesse
- Weaviate
- Yellowbrick
- AirFlow
- AlloyDB
- APOLLO
- Azure Cosmos DB
- BlazingDB
- Cassandra
- Chronon
- CockroachDB
- CouchDB
- Daft
- Datometry
- dbt
- Dolt
- Druid
- DVMS
- Exon
- Fauna
- Feldera
- Fluree
- Gaia
- Google Spanner
- GreptimeDB
- HorizonDB
- Impala
- kdb
- Lakebase
- Litestream
- MapD
- MemSQL
- Modin
- Mooncake
- MySQL
- NoisePage
- OceanBase
- Oracle
- OxQL
- Pinot
- Polaris
- PRQL
- QuasarDB
- Redshift
- RocksDB
- rqlite
- ScyllaDB
- Sirius
- Smooth
- Spice.ai
- SplinterDB
- SQLancer
- Stardog
- Summingbird
- Technical University of Munich
- TiDB
- TimescaleDB
- TopK
- Turso
- Vertica
- VoltDB
- WiredTiger
- YugabyteDB
- Akamas
- Anna
- Arrow
- Berkeley DB
- Bodo
- Chaos Mesh
- Citus
- Confluent
- CrateDB
- Databricks
- Datomic
- Debezium
- Doris
- DSQL
- EdgeDB
- eXtremeDB
- FeatureBase
- Firebolt
- Fluss
- Gel
- GoogleSQL
- HarperDB
- Hudi
- InfluxDB
- Kinetica
- LanceDB
- LMDB
- MariaDB
- Microsoft SQL Server
- MonetDB
- MotherDuck
- Napa
- Noria
- OneWill
- OtterTune
- ParadeDB
- Pixeltable
- PostgresML
- Qdrant
- QuestDB
- RelationalAI
- Rockset
- SalesForce
- Sentry
- sled
- Snowflake
- SpiceDB
- SQL Anywhere
- SQLite
- StarRocks
- Swarm64
- TeraData
- TigerBeetle
- Tokutek
- Trino
- Umbra
- VillageSQL
- Vortex
- XTDB
- Aerospike
- AlloyDB
- Arrow
- BigQuery
- Cassandra
- Citus
- Convex
- Daft
- Datomic
- Delta Lake
- Druid
- EdgeDB
- FASTER
- Feldera
- Fluss
- GlareDB
- GreptimeDB
- Hudi
- Jepsen
- Lakebase
- LMDB
- Materialize
- Modin
- MotherDuck
- Neon
- OceanBase
- OtterTune
- Pinecone
- Polaris
- Qdrant
- RavenDB
- RocksDB
- SalesForce
- SingleStore
- Smooth
- SpiceDB
- SQL Server
- Stardog
- Swarm64
- TerminusDB
- TimescaleDB
- Trino
- Velox
- VoltDB
- XTDB
- AirFlow
- Anna
- Aurora DSQL
- BlazingDB
- Chaos Mesh
- ClickHouse
- CouchDB
- Databricks
- DB9
- Dolt
- DSQL
- EraDB
- Fauna
- Firebolt
- FoundationDB
- Google Spanner
- HarperDB
- Iceberg
- kdb
- LanceDB
- Malloy
- MemSQL
- MonetDB
- Multigres
- NoisePage
- OneWill
- Oxla
- Pinot
- PostgresML
- QMDB
- Redshift
- Rockset
- Samza
- Sirius
- Snowflake
- Splice Machine
- SQLancer
- StarRocks
- Synnada
- TiDB
- Tokutek
- turbopuffer
- Vertica
- Vortex
- Yellowbrick
- Akamas
- ApertureDB
- Azure Cosmos DB
- Bodo
- Chroma
- CockroachDB
- CrateDB
- DataFusion
- dbt
- Doris
- DuckDB
- Exon
- FeatureBase
- Floe
- Gaia
- GoogleSQL
- Heron
- Impala
- Kinetica
- LeanStore
- MapD
- Microsoft SQL Server
- MongoDB
- MySQL
- Noria
- OpenDAL
- OxQL
- Pixeltable
- PostgreSQL
- QuasarDB
- RelationalAI
- RonDB
- ScyllaDB
- sled
- SpacetimeDB
- SplinterDB
- SQLite
- Striim
- Technical University of Munich
- TigerBeetle
- TonicDB
- Turso
- VillageSQL
- Weaviate
- YugabyteDB
- Alibaba
- APOLLO
- Berkeley DB
- Brytlyt
- Chronon
- Confluent
- CrocodileDB
- Datometry
- Debezium
- Dremio
- DVMS
- eXtremeDB
- Featureform
- Fluree
- Gel
- Greenplum
- HorizonDB
- InfluxDB
- ksqlDB
- Litestream
- MariaDB
- Milvus
- Mooncake
- Napa
- NuoDB
- Oracle
- ParadeDB
- PlanetScale
- PRQL
- QuestDB
- RisingWave
- rqlite
- Sentry
- SLOG
- Spice.ai
- SQL Anywhere
- SQream
- Summingbird
- TeraData
- TileDB
- TopK
- Umbra
- Vitesse
- WiredTiger
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 10
2024
[Fall 2024] Databricks: Introduction to Mosaic AI Vector Search
- Speaker:
- Ankit Vij
- System:
- Databricks
This tech talk will deep dive into some of the most interesting challenges being solved at Databricks. Read More
Aug 21
2024
LSM Management and Using LSM Immutability for Data Virtualization (Vaibhav Arora)
- Speaker:
- Vaibhav Arora
LSM (Log-Structured Merge) trees are now the bedrock of many storage engines and datastores like RocksDB, HBase, Cassandra etc. They provide the ability to avoid random-writes, and provide immutability. Data is organized in multiple-levels that are exponentially increasing in size. Each data mutation writes a new version of an object, and background processes named merge/compaction continuously remove the unused versions,... Read More
Jun 26
2024
Leveraging Generative AI with Oracle AI Vector Search (Shasank Chavan)
- Speaker:
- Shasank Chavan
- System:
- Oracle
AI Vector Search in Oracle 23ai is a new, transformative way to intelligently search through your unstructured business data efficiently, and accurately, by using AI techniques to match on the semantics, or meaning, of the underlying data. With the inclusion of a new VECTOR datatype, new approximate search indexes, and new SQL operators and extensions, enterprise companies can quickly and... Read More
Apr 24
2024
[Spring 2024] Beyond SQL: Dataframes in the Database (Devin Petersohn)
- Speaker:
- Devin Petersohn
- System:
- Modin
Dataframes are popular tools for interacting with and exploring data, but they are not as well understood nor as deeply studied as databases. Python's pandas. and Apache Spark are two of the most popular dataframes in use by data practitioners, but even these are extremely different from each other in terms of guarantees and user expectations. In this talk, we... Read More
Apr 17
2024
[Spring 2024] Manufacturing AI Applications (Anthony Tomasic)
- Speaker:
- Anthony Tomasic
Developing AI applications is costly and difficult and recent trends have only intensified these challenges. Developers use a bottom-up approach, focusing on the nitty-gritty of integration and infrastructure, which leads to a complex "blob" of code. Changes to this blob are risky due to the intricate web of dependencies. Fort Alto has fundamentally rethought the application development process with a... Read More
Apr 5
2024
PhD Defense: On Embedding Database Management System Logic in Operating Systems via Restricted Programming Environments (Matt Butrovich)
- Speaker:
- Matt Butrovich
The rise in computer storage and network performance means that disk I/O and network communication are often no longer bottlenecks in database management systems (DBMSs). Instead, the overheads associated with operating system (OS) services (e.g., system calls, thread scheduling, and data movement from kernel-space) limit query processing responsiveness. User-space applications can elide these overheads with a kernel-bypass design. However, extracting... Read More
Mar 14
2024
[Spring 2024] Towards a Systematic Framework for Index Structure Design (Dong Xie)
- Speaker:
- Dong Xie
Index structures are at the database management systems' core to facilitate efficient data access. Due to the constant changes in application requirements and hardware trends, people are going through exhaustive and painstaking work designing/tailoring new index structures to catch up. In this talk, I will show a vision of a systematic index structure design framework that will allow index designers... Read More
Feb 29
2024
[Spring 2024] Embedding Database Logic in the Operating System Is Finally a Good Idea (Matt Butrovich)
- Speaker:
- Matt Butrovich
The rise in computer storage and network performance means that disk I/O and network communication are often no longer bottlenecks in database management systems (DBMSs). Instead, the overheads associated with operating system (OS) services (e.g., system calls, thread scheduling, and data movement from kernel-space) limit query processing responsiveness. To avoid these overheads, user-space applications prioritizing performance over simplicity can elide... Read More
Jan 5
2024
[Winter 2023] Survey and Evaluation of Database Management System Extensibility (Abi Kim)
- Speaker:
- Abi Kim
Database management system (DBMS) extensibility is a feature which enables users to extend the DBMS with user software. However, the DBMS extensibility environment is fraught with perils, and DBMS developers have to resort to unspecified methods of developing extensions, including copying core DBMS source code and casing between different versions of the DBMS. Extending a DBMS to support new functionality... Read More