NewSQL - The Future of Databases?
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NewSQL databases seek to provide the same scalable performance as NoSQL databases for online transaction processing workloads, while still maintaining the ACID guarantees of a traditional SQL database. NewSQL databases use new architectures like multi-version concurrency control and partition-level locking to allow for horizontal scaling and high availability without sacrificing consistency. They also provide highly optimized SQL engines to query data in a distributed environment.
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NewSQL - The Future of Databases?
- 1. NewSQL The Future of Databases? 1 Elvis Saravia & Dau-Heng Hsu 23/11/2015
- 2. Outline ● Introducing NewSQL ● Architecture ● Drawbacks of NewSQL ● Conclusion ● Q&A 2
- 3. What is NewSQL? “...NewSQL is a class of modern relational database management systems that seek to provide the same scalable performance of NoSQL systems for online transaction processing (read-write) workloads while still maintaining the ACID guarantees of a traditional database system…” 3 - Wikipedia
- 4. OLTP (Online Transaction Processing) 4 Old OLTP New OLTP OldSQL for New OLTP ● Too slow ● Does not Scale NoSQL for New OLTP ● Cannot guarantee consistency NewSQL for New OLTP ● Fast, Scalable and consistent ● Supports SQL
- 5. State of the Database 5 ACID transactions SQL support Standardized Horizontal Scaling High Availability Horizontal Scaling High Availability ACID transactions SQL support Standardized ACID transactions Horizontal Scaling High Availability SQL support Standardized RDBMS (OLDSQL) NOSQL NEWSQL
- 6. A more comprehensive look 6 ● Traditional OldSQL ○ SQL ○ ACID compliant ○ Re-write and re-architect to scale (Sharding, Denormalizing, Distributed Caching) ● NoSQL ○ Scalability and Availability ○ Schema-less (great for non-transactional systems) ○ Give up SQL ○ Give up ACID transactions (not fit for OLTP systems) ● NewSQL ○ SQL ○ Scalable, shared nothing architecture ○ ACID compliant ○ Schema
- 7. Why do we need NewSQL (Summary)? ● Provide the same scalable performance of NoSQL for OLTP, and still maintaining the ACID. ● With relations and SQL. 7
- 8. 8
- 9. NewSQL Categories 1. New architectures: VoltDB, NuoDB 2. SQL engines: TokuDB, ScaleDB 3. Transparent sharding: ScaleBase, dbShards 9 Source: Wikipedia
- 10. 1. Architecture: New architectures ● Provide concurrency control. ● Traditional relational db concurrency control ○ 2 phase locking ● Newsql db concurrency control ○ MVCC (Multi Version Concurrency Control) ○ Basic Timestamp Concurrency Control ○ Optimistic Concurrency Control ○ T/O with Partition-Level Locking ○ And others. ● e.g. Google Spanner, VoltDB, MemSQL 10
- 11. MVCC (Multi Version Concurrency Control) ● Read data without blocking update. ● Each transaction keeps a snapshot. ● By reading the snapshot, gets a consistent view of the database. ● Cost: ○ Garbage collection on old snapshot. 11New architectures snapshots time
- 12. Basic Timestamp Concurrency Control ● Timestamp on tuple. ● For read or write: ○ rejects if the timestamp is less than the timestamp of the last write to that tuple. ● For a write operation: ○ rejects if the timestamp is less than the timestamp of the last read to that tuple. ● Cost: ○ Each site maintains a logical clock, need to be accurate. 12New architectures
- 13. Optimistic Concurrency Control ● Tracks the read/write transaction; Stores all write operations in private workspace. ● The system determines whether that transaction’s read set overlaps with the write set of any concurrent transactions. ● Transactions write their updates to shared memory only at commit time, the contention period is short. ● Cost: ○ Rollback 13New architectures
- 14. T/O with Partition-Level Locking ● Database is divided into disjoint subsets, called partitions. ● Partition ○ Lock. ○ Single-threaded execution engine. ● Apply timestamp on a transaction, and add to queues. ● Execution the oldest timestamp transaction in the queue. 14New architectures
- 15. 2. Architecture: SQL engines ● Provide highly optimized storage engines for SQL. ○ use MySQL Cluster as an example. ● Separate nodes into 3 kinds of node ○ Data node ■ Store the data ○ Management node ■ Configuration and monitoring of the cluster. ○ Application node or SQL node ■ Connects to all of the data nodes and perform data storage and retrieval. ● Consistency will be controlled by Application nodes. 15
- 16. 3. Architecture: Transparent sharding ● Use sharding middleware. ● All the node can connect to middleware. ● Middleware will control all the process to ensure the consistency. ● e.g. dbShards and ScaleBase. 16
- 17. Main drawback ● Write latency. ○ With the concurrency control, need more time to make sure the data is consistent. ● Can use in-memory mechanism to help us reduce latency, but restricted by memory size. 17Source: http://www.planetcassandra.org/nosql-performance-benchmarks/ Write latency for workload Read/Write
- 18. Conclusion ● A database trend to watch ● NewSQL is ACID compliant, SQL based, scalable, distributed, highly available RDBMS system ● NewSQL databases are becoming more demanded due to the rise of data-oriented industries (e.g. IoT) 18 Something to think about: In fact, both NoSQL and NewSQL databases can offer a degree of consistency, and availability, as well as partition tolerance.
- 19. References 1. http://www.informationweek.com/big-data/big-data-analytics/16-nosql-ne wsql-databases-to-watch/d/d-id/1269559 2. https://en.wikipedia.org/wiki/NewSQL 3. https://github.com/cockroachdb/cockroach 4. https://voltdb.com/ 5. https://451research.com 19
- 20. Q&A 20