- Aerospike
- Alibaba
- Anna
- APOLLO
- Azure Cosmos DB
- BigQuery
- Bodo
- Cassandra
- Chroma
- ClickHouse
- Confluent
- CouchDB
- CrocodileDB
- DataFusion
- Datomic
- Debezium
- Dremio
- DuckDB
- EdgeDB
- Exon
- FASTER
- FeatureBase
- Feldera
- Fluree
- Gaia
- GlareDB
- GoogleSQL
- GreptimeDB
- Heron
- InfluxDB
- kdb
- ksqlDB
- LeanStore
- LMDB
- MapD
- Materialize
- Milvus
- MonetDB
- MySQL
- Neon
- Noria
- OceanBase
- Oracle
- OxQL
- Pinecone
- PlanetScale
- 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
- Weaviate
- Yellowbrick
- Akamas
- AlloyDB
- ApertureDB
- Arrow
- Berkeley DB
- BlazingDB
- Brytlyt
- Chaos Mesh
- Citus
- CockroachDB
- Convex
- CrateDB
- Databricks
- Datometry
- dbt
- Dolt
- Druid
- DVMS
- EraDB
- eXtremeDB
- Fauna
- Featureform
- Firebolt
- FoundationDB
- Gel
- Google Spanner
- Greenplum
- HarperDB
- Impala
- Jepsen
- Kinetica
- LanceDB
- Litestream
- Malloy
- MariaDB
- MemSQL
- Modin
- MongoDB
- Napa
- NoisePage
- NuoDB
- OpenDAL
- OtterTune
- ParadeDB
- Pinot
- 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
- WiredTiger
- YugabyteDB
- Aerospike
- AlloyDB
- APOLLO
- Berkeley DB
- Bodo
- Chaos Mesh
- ClickHouse
- Convex
- CrocodileDB
- Datometry
- Debezium
- Druid
- EdgeDB
- eXtremeDB
- FeatureBase
- Firebolt
- Gaia
- Google Spanner
- GreptimeDB
- Impala
- kdb
- LanceDB
- LMDB
- MariaDB
- Milvus
- MongoDB
- Neon
- NuoDB
- Oracle
- ParadeDB
- PlanetScale
- PRQL
- QuasarDB
- Redshift
- RocksDB
- rqlite
- ScyllaDB
- SLOG
- Spice.ai
- SplinterDB
- SQLancer
- Stardog
- Summingbird
- Technical University of Munich
- TigerBeetle
- Tokutek
- Velox
- VoltDB
- Yellowbrick
- Akamas
- Anna
- Arrow
- BigQuery
- Brytlyt
- Chroma
- CockroachDB
- CouchDB
- Databricks
- Datomic
- Dolt
- DuckDB
- EraDB
- FASTER
- Featureform
- Fluree
- Gel
- GoogleSQL
- HarperDB
- InfluxDB
- Kinetica
- LeanStore
- Malloy
- Materialize
- Modin
- MySQL
- NoisePage
- OceanBase
- OtterTune
- Pinecone
- PostgresML
- Qdrant
- QuestDB
- RelationalAI
- Rockset
- SalesForce
- SingleStore
- Smooth
- SpiceDB
- SQL Anywhere
- SQLite
- StarRocks
- Swarm64
- TerminusDB
- TileDB
- Trino
- Vertica
- Weaviate
- YugabyteDB
- Alibaba
- ApertureDB
- Azure Cosmos DB
- BlazingDB
- Cassandra
- Citus
- Confluent
- CrateDB
- DataFusion
- dbt
- Dremio
- DVMS
- Exon
- Fauna
- Feldera
- FoundationDB
- GlareDB
- Greenplum
- Heron
- Jepsen
- ksqlDB
- Litestream
- MapD
- MemSQL
- MonetDB
- Napa
- Noria
- OpenDAL
- OxQL
- Pinot
- PostgreSQL
- QMDB
- RavenDB
- RisingWave
- RonDB
- Samza
- sled
- Snowflake
- Splice Machine
- SQL Server
- SQream
- Striim
- Synnada
- TiDB
- TimescaleDB
- Umbra
- Vitesse
- WiredTiger
- Aerospike
- Anna
- Azure Cosmos DB
- Bodo
- Chroma
- Confluent
- CrocodileDB
- Datomic
- Dremio
- EdgeDB
- FASTER
- Feldera
- Gaia
- GoogleSQL
- Heron
- kdb
- LeanStore
- MapD
- Milvus
- MySQL
- Noria
- Oracle
- Pinecone
- PostgreSQL
- QuasarDB
- RelationalAI
- RonDB
- ScyllaDB
- Smooth
- Splice Machine
- SQLancer
- StarRocks
- Synnada
- TigerBeetle
- Trino
- Vitesse
- Yellowbrick
- Akamas
- ApertureDB
- Berkeley DB
- Brytlyt
- Citus
- Convex
- Databricks
- dbt
- Druid
- EraDB
- Fauna
- Firebolt
- Gel
- Greenplum
- Impala
- Kinetica
- Litestream
- MariaDB
- Modin
- Napa
- NuoDB
- OtterTune
- Pinot
- PRQL
- QuestDB
- RisingWave
- rqlite
- SingleStore
- Snowflake
- SplinterDB
- SQLite
- Striim
- Technical University of Munich
- TileDB
- Umbra
- VoltDB
- YugabyteDB
- Alibaba
- APOLLO
- BigQuery
- Cassandra
- ClickHouse
- CouchDB
- DataFusion
- Debezium
- DuckDB
- Exon
- FeatureBase
- Fluree
- GlareDB
- GreptimeDB
- InfluxDB
- ksqlDB
- LMDB
- Materialize
- MonetDB
- Neon
- OceanBase
- OxQL
- PlanetScale
- Qdrant
- RavenDB
- RocksDB
- SalesForce
- sled
- Spice.ai
- SQL Anywhere
- SQream
- Summingbird
- TerminusDB
- TimescaleDB
- Velox
- Weaviate
- AlloyDB
- Arrow
- BlazingDB
- Chaos Mesh
- CockroachDB
- CrateDB
- Datometry
- Dolt
- DVMS
- eXtremeDB
- Featureform
- FoundationDB
- Google Spanner
- HarperDB
- Jepsen
- LanceDB
- Malloy
- MemSQL
- MongoDB
- NoisePage
- OpenDAL
- ParadeDB
- PostgresML
- QMDB
- Redshift
- Rockset
- Samza
- SLOG
- SpiceDB
- SQL Server
- Stardog
- Swarm64
- TiDB
- Tokutek
- Vertica
- WiredTiger
Nov 14
2013
Realtime and Batch Data Processing @ Twitter (Dmitriy Ryaboy)
- Speaker:
- Dmitriy Ryaboy
- System:
- Summingbird
Summingbird, an open-source project recently released by Twitter, allows engineers to easily build data processing pipelines that work both in a streaming context provided by Twitter Storm, and in offline batch context through Apache Hadoop. This talk will cover the practical motivation for building such a thing, and explain the core Summingbird architecture and components. Read More
Oct 24
2013
Beyond Bigtable: Challenges in Cassandra 2.0 (Jonathan Ellis)
- Speaker:
- Jonathan Ellis
- System:
- Cassandra
Cassandra has fulfilled its original design as a Bigtable/Dynamo hybrid and is moving beyond it with the release of 2.0 last month. (I have annotated the original Cassandra LADIS paper with comparisons to modern Apache Cassandra at [1].) I will talk about integrating Paxos with an eventually consistent system, using cardinality estimation to improve compaction efficiency, and improving request isolation... Read More
Oct 10
2013
The New Era of Data Management: MongoDB and Document Databases (Dwight Merriman)
- Speaker:
- Dwight Merriman
- System:
- MongoDB
SQL databases have been the dominant form of data management since the late 1970's. However, computing and technology have evolved, leading to an influx of data and new systems to manage it. For this new generation, "Document Databases" quickly emerged as a popular solution and became widely used among companies of all sizes. Using MongoDB as the example, we'll look... Read More