- Aerospike
- Akamas
- AlloyDB
- Antithesis
- 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
- 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
- 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
- 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
- Antithesis
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- OtterTune
- Pinecone
- Polaris
- Qdrant
- RavenDB
- RocksDB
- SalesForce
- SingleStore
- Smooth
- SpiceDB
- SQL Server
- Stardog
- Swarm64
- TerminusDB
- TimescaleDB
- Trino
- Velox
- VoltDB
- XTDB
- AirFlow
- Anna
- 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
- Oxla
- Pinot
- PostgresML
- QMDB
- Redshift
- Rockset
- Samza
- Sirius
- Snowflake
- Splice Machine
- SQLancer
- StarRocks
- Synnada
- TiDB
- Tokutek
- turbopuffer
- Vertica
- Vortex
- Yellowbrick
- Akamas
- Antithesis
- 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
- OpenDAL
- OxQL
- Pixeltable
- PostgreSQL
- QuasarDB
- RelationalAI
- RonDB
- ScyllaDB
- sled
- SpacetimeDB
- SplinterDB
- SQLite
- Striim
- Technical University of Munich
- TigerBeetle
- TonicDB
- Turso
- VillageSQL
- Weaviate
- YugabyteDB
- Alibaba
- 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
- Oracle
- ParadeDB
- PlanetScale
- PRQL
- QuestDB
- RisingWave
- rqlite
- Sentry
- SLOG
- Spice.ai
- SQL Anywhere
- SQream
- Summingbird
- TeraData
- TileDB
- TopK
- Umbra
- Vitesse
- WiredTiger
Aug 24
2020
ScyllaDB — No-Compromise Performance
- Speaker:
- Avi Kivity
- System:
- ScyllaDB
- Video:
- YouTube
ScyllaDB is a distributed NoSQL database that provides high availability, multiple consistency models, and high performance. This talk will cover how ScyllaDB approaches performance: thread-per-core, fully asynchronous operation, and kernel bypass. This talk is part of the Quarantine Database Tech Talk Seminar Series. Zoom Link: https://cmu.zoom.us/j/562649242 (Password 264771) Read More
Aug 17
2020
TerminusDB: Building a Native Revision Control DB from Scratch
- Speaker:
- Gavin Mendel-Gleason
- System:
- TerminusDB
- Video:
- YouTube
Revision control and CI/CD has completely transformed the way we write and deliver software. Yet data management has not kept pace with these changes. Data assets are still managed using RDBMSs, or worse, with CSVs or Excel spreadsheets. Since many software applications rely on data assets, this presents a serious problem for data-driven software. TerminusDB is a graph database which... Read More
Aug 10
2020
Splice Machine – An HTAP DB at Scale
- Speakers:
- Daniel Gómez Ferro , Yi Xia
- System:
- Splice Machine
- Video:
- YouTube
Emerging modern applications routinely depend on data at scale for AI and ML and therefore require HTAP (Hybrid Transactional/Analytical Processing) database systems to make real-time business decisions. In this talk, we would like to introduce Splice Machine, an HTAP DB at scale, our mission and architecture. We will also dive into the topics of our transaction mechanism, query optimization and... Read More
Aug 3
2020
YugabyteDB: Bringing Together the Best of Amazon Aurora and Google Spanner
- Speaker:
- Karthik Ranganathan
- System:
- YugabyteDB
- Video:
- YouTube
PostgreSQL, a single-node open-source RDBMS, is widely adopted for its powerful set of features. However, PostgreSQL is not built to be used as a cloud-native database, and therefore cannot inherently survive failures, scale horizontally or support geo-distributed deployments. While Amazon Aurora has modified the subsystem of PostgreSQL that writes to disk along with simplifying async replication to make the database resilient... Read More
Jul 27
2020
Black-box Isolation Checking with Elle
- Speaker:
- Kyle Kingsbury
- System:
- Jepsen
- Video:
- YouTube
Databases are awful. They lose information, corrupt state, and do other terrible things, both by design and by accident. You'd think that *testing* databases to see how awful they are would help make them better, but it turns out that testing most of the useful database safety properties is *also* awful. We came up with a better way to test... Read More
Jul 24
2020
MS Thesis Defense: Filter Representation in Vectorized Query Execution (Amadou Ngom)
- Speaker:
- Amadou Ngom
Advances in memory capacity have allowed Database Management Systems (DBMSs) to store large amounts of data in memory, thereby shifting the performance bottleneck of query execution from disk accesses to CPU efficiency (i.e., instruction count and cycles per instruction). One technique used to achieve such efficiency in analytical applications is batch-oriented processing or vectorization: it reduces interpretation overhead, improves cache... Read More
Jul 20
2020
Rockset: Realtime Indexing for fast queries on massive semi-structured data
- Speaker:
- Dhruba Borthakur
- System:
- Rockset
- Video:
- YouTube
Rockset is a realtime indexing database that powers fast SQL over semi-structured data such as JSON, Parquet, or XML without requiring any schematization. All data loaded into Rockset are automatically indexed and a fully featured SQL engine powers fast queries over semi-structured data without requiring any database tuning. Rockset exploits the hardware fluidity available in the cloud and automatically grows... Read More
Jul 13
2020
Astra: How we built a Cassandra-as-a-Service
- Speakers:
- Jim McCollom , Jeff Carpenter
- System:
- Cassandra
- Video:
- YouTube
At DataStax, we’ve been on a multi-year journey to bring a Cassandra DBaaS to the market, culminating in the GA of Astra in May 2020. In this talk, we’ll share our successes and failures through the iterative journey to GA, our current Kubernetes based architecture, how we built scalability and reliability into the platform, and how Cassandra’s architecture and implementation... Read More
Jul 6
2020
Another Relational Database, Why and How
- Speaker:
- Oscar Batori & Zach Musgrave
- System:
- Dolt
- Video:
- YouTube
There are a lot of relational database, so a fair question is why we decided to create a new one. The primary reason is trade-offs. Relational database are optimized for storing a single version of the truth and providing it or updating it with maximum efficiency. More succinctly they are optimized for being good OLTP stores. They are not optimized... Read More
Jun 29
2020
[DB Seminar] Spring 2020 DB Group: Linux 4.x Tracing (Pre-Recorded)
- Speaker:
- Brendan Gregg
There is no invited speaker today. We will instead watch this video together: Linux 4.x Tracing: Performance Analysis with bcc/BPF (eBPF) Brendan Gregg https://youtu.be/w8nFRoFJ6EQ Zoom Password: 264771 Read More