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Distributed SQL Architecture | Cloud Database | Distributed Database
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In this video Jim Walker, our VP of product marketing, discusses all the nuances of Distributed SQL database architecture and how it fits in the world of Cloud Databases or Distributed Databases.
00:00 Why does Distributed SQL need to exist?
1:34 What is a Relational Database for the cloud?
3:04 What is CockroachDB?
4:20 Important CockroachDB concept: Any node can service a query.
5:17 How does CockroachDB compare to Cassandra?
6:30 What is the Architecture of CockroachDB?
7:14 What is the difference between CockroachDB and a normal relational database?
8:07 Why is it important that CockroachDB is implemented as a KV store?
9:35 Example of a typical table in CockroachDB
10:37 What are ranges in CockroachDB? (256 megabyte ranges - think of ranges as a shard)
12:04 How does CockroachDB automate sharding?
13:27 Is there a maximum overall DB size for each table?
14:30 RAFT - Distributed consensus protocol in CockroachDB
16:05 RAFT, Transactions and Replication in CockroachDB
18:22 How does CockroachDB guarantee that data is always correct?
19:15 Where does CockroachDB place replicas?
19:52 How does data replication work in CockroachDB? (And why is it special?)
22:27 How does CockroachDB lower latency by geo-partitioning data?
23:40 What is the biggest challenge in Distributed Systems? The Speed of Light.
24:26 Every node can deliver the DB-Console to you
25:26 How does CockroachDB survive failures?
26:56 How does CockroachDB guarantee consistent transactions at scale?
30:25 The importance of retry logic
30:58 Why does CockroachDB require writes to 2 of 3 nodes?
31:34 How does distributed SQL execution work?
33:30 How do I use the Cost Based Optimizer?
34:35 Latency in Distributed Databases
37:15 What is the 100-millisecond rule?
41:42 Distributed Database Transaction Performance
44:50 How CockroachDB competes with the Speed of Light
47:53 Should I deploy CockroachDB on Kubernetes?
#DistributedSQL #CloudDatabase #DistibutedDatabase #RDBMS #CockroachDB
Relevant Links:
00:00 Why does Distributed SQL need to exist?
1:34 What is a Relational Database for the cloud?
3:04 What is CockroachDB?
4:20 Important CockroachDB concept: Any node can service a query.
5:17 How does CockroachDB compare to Cassandra?
6:30 What is the Architecture of CockroachDB?
7:14 What is the difference between CockroachDB and a normal relational database?
8:07 Why is it important that CockroachDB is implemented as a KV store?
9:35 Example of a typical table in CockroachDB
10:37 What are ranges in CockroachDB? (256 megabyte ranges - think of ranges as a shard)
12:04 How does CockroachDB automate sharding?
13:27 Is there a maximum overall DB size for each table?
14:30 RAFT - Distributed consensus protocol in CockroachDB
16:05 RAFT, Transactions and Replication in CockroachDB
18:22 How does CockroachDB guarantee that data is always correct?
19:15 Where does CockroachDB place replicas?
19:52 How does data replication work in CockroachDB? (And why is it special?)
22:27 How does CockroachDB lower latency by geo-partitioning data?
23:40 What is the biggest challenge in Distributed Systems? The Speed of Light.
24:26 Every node can deliver the DB-Console to you
25:26 How does CockroachDB survive failures?
26:56 How does CockroachDB guarantee consistent transactions at scale?
30:25 The importance of retry logic
30:58 Why does CockroachDB require writes to 2 of 3 nodes?
31:34 How does distributed SQL execution work?
33:30 How do I use the Cost Based Optimizer?
34:35 Latency in Distributed Databases
37:15 What is the 100-millisecond rule?
41:42 Distributed Database Transaction Performance
44:50 How CockroachDB competes with the Speed of Light
47:53 Should I deploy CockroachDB on Kubernetes?
#DistributedSQL #CloudDatabase #DistibutedDatabase #RDBMS #CockroachDB
Relevant Links:
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