Aws Summit Berlin 2013 - Understanding database options on AWS
Download as PPTX, PDF1 like2,388 views
With AWS you can choose the right database for the right job. Given the myriad of choices, from relational databases to non-relational stores, this session will profile details and examples of some of the choices available to you (MySQL, RDS, Elasticache, Redis, Cassandra, MongoDB and DynamoDB), with details on real world deployments from customers using Amazon RDS, ElastiCache and DynamoDB.
Ad
More Related Content
Viewers also liked (9)
Similar to Aws Summit Berlin 2013 - Understanding database options on AWS (8)
Ad
More from AWS Germany (20)
Ad
Recently uploaded (20)
Aws Summit Berlin 2013 - Understanding database options on AWS
- 1. Jan Borch - AWS Solutions Architect Understanding Database Options on AWS Jan Borch #awssummit Berlin
- 2. We want to make it easy for you to start 1. Zero to Application in ____ Minutes 2. Zero to Millions of users in ____ Days 3. Zero to “Profits!” ASAP
- 3. Spot the critical component!
- 5. Spectrum of options on AWS SQL NoSQL Low Cost High Cost Do-it-yourself Fully Managed Not available on AWS
- 6. Spectrum of options on AWS SQL NoSQL Do-it-yourself Fully Managed
- 7. RDS - MySQL - Oracle - SQL Server MySQL Oracle SQL Server PostgreSQL Your favorite RDBMS Spectrum of options on AWS SQL NoSQL Do-it-yourself Fully Managed
- 8. Spectrum of options on AWS SQL NoSQL Do-it-yourself Fully Managed MongoDB Cassandra Redis Memcached … Amazon DynamoDB Amazon ElastiCache
- 9. Thinking about the questions Should I use SQL or NoSQL? Should I use MySQL on EC2 or RDS? Should I use MongoDB, Cassandra , or DynamoDB? Should I use Redis, Memcached, or ElastiCache? ?
- 10. Actually, thinking about the right questions What are my scale and latency needs? What are my transactional and consistency needs? What are my read/write, storage and IOPS needs? What are my time to market and server control needs? ?
- 11. Focus on your application
- 12. Option 1: Run your databases on EC2
- 13. Amazon Elastic Compute Cloud Amazon EC2
- 14. Virtual core: 1 Memory: 1.7 GiB I/O performance: Moderate m1.small cc2.8xlarge Virtual core: 32 - 2 x Intel Xeon Memory: 60,5 GiB I/O performance: 10 Gbit cr1.8xlarge Virtual core: 32 - 2 x Intel Xeon Memory: 240 GiB I/O performance: 10 Gbit SSD Instance store: 240 GB cr1.8xlarge Virtual core: 16 Memory: 60.5 GiB I/O performance: 10 Gbit SSD Instance store: 2 x 1TB cr1.8xlarge Virtual core: 16 Memory: 117 GiB I/O performance: 10 Gbit Instance store: 24 x 2TB
- 16. Choose an Amazon Machine Image
- 17. Leverage AWS services EBS storage Volumes with EBS Snapshots S3 for backups (for example Oracle RMAN) Automation with AWS API or CloudFormation
- 18. Option 2: Let AWS manage my databases
- 19. backup & recovery, data load & unload performance tuning 25%40% 5% 5% scripting & coding security planning install, upgrade, patch and migrate documentation, licensing & training differentiated effort increases the uniqueness of an application Why Managed Databases?
- 20. We believe in choice One size does not fit all Traditional Apps Relational DB Needs High Performance, High Scale Data Warehouses New Web Apps Massive Scalability Amazon RDS Amazon ElasticCache Amazon DynamoeDB Amazon Redshift
- 21. Option 2.1: Managed SQL database
- 22. Amazon Relational Database Services AmazonRDS RDS is a fully managed relational database service that is simple to deploy, easy to scale, reliable and cost-effective
- 23. Choice of database options
- 24. Rapid deployment via Web Console
- 26. Push Button Scaling Scale … • vertically up or down • Storage vertically
- 27. Price reduction High Availability: Multi-AZ Deployments Multi AZ price reductions ranging from 15% to 32%
- 28. A few clicks or one API call
- 29. Horizontal Scaling with Read Replicas New Features • Endpoint Renaming • ReadReplica to master promotion
- 30. A few clicks or one API call
- 32. Security Oracle Native Network Encryption and Transparent Data Encryption on Oracle EE SSL support for SQL Server and mysql
- 33. Amazon RDS Configuration Improve Availability Increase Throughput Reduce Latency Push-Button Scaling Multi-AZ Read Replicas Provisioned IOPS Read ReplicasPush-Button Scaling Provisioned IOPS Region Multi-AZ Availability Zone Availability Zone Availability and performance options
- 34. Use case
- 35. Who is succeeding with RDS? Thousands of developers use RDS every single day Gaming Web Apps Mobile/Social Media
- 36. Amazon Elastic Cache Amazon ElastiCache is a fully managed Memcached-compatible caching service
- 37. Option 2.2: Managed noSQL database
- 38. Amazon DynamoDB Amazon DynamoDB is a fully managed NoSQL database service
- 39. Single digit millisecond latency. Backed on solid-state drives. Consistent, predictable performance
- 40. No table size limits. Unlimited storage No downtime. Seamless scalability
- 41. Consistent, disk only writes. Replication across data centers and availability zones. Durable
- 42. Without the operational burden. managed by DynamoDB
- 43. Three click or on API call
- 44. Reserve IOPS for reads and writes. Scale up for down at any time. Provisioned throughput.
- 45. Pay per capacity unit READ Capacity Units = Size of item (KB) x read per second Consistent read: $0.0065 for 50 read units Eventually consistent reads: $0.0065 for 100 read units WRITE Capacity Units = Size of item (KB) x write per second $0.0065 for 10 write units
- 46. Reserved capacity Up to 53% for 1 year reservation Up to 76% for 3 year reservation
- 47. Transactions Item level transactions only Puts, updates and deletes are ACID Atomic increment and decrement Conditional writes
- 48. Read Consistency Strong or eventually consistent reads Same latency expectations for strong Mix and match at „read time‟
- 49. Data Modeling Tables do not require a formal schema Items are an arbitrarily sized hash.
- 50. id = 100 date = 2012-05-16-09- 00-10 total = 25.00 id = 101 date = 2012-05-15-15- 00-11 total = 35.00 id = 101 date = 2012-05-16-12- 00-10 total = 100.00 id = 102 date = 2012-03-20-18- 23-10 total = 20.00 id = 102 date = 2012-03-20-18- 23-10 total = 120.00 Data modeling Table
- 51. id = 100 date = 2012-05-16-09- 00-10 total = 25.00 id = 101 date = 2012-05-15-15- 00-11 total = 35.00 id = 101 date = 2012-05-16-12- 00-10 total = 100.00 id = 102 date = 2012-03-20-18- 23-10 total = 20.00 id = 102 date = 2012-03-20-18- 23-10 total = 120.00 Data modeling Item
- 52. id = 100 date = 2012-05-16-09- 00-10 total = 25.00 id = 101 date = 2012-05-15-15- 00-11 total = 35.00 id = 101 date = 2012-05-16-12- 00-10 total = 100.00 id = 102 date = 2012-03-20-18- 23-10 total = 20.00 id = 102 date = 2012-03-20-18- 23-10 total = 120.00 Data modeling Attributes
- 53. Items are indexed by primary and secondary keys Primary keys can be composite Secondary keys are local to the table Indexing
- 55. ID Date Total Hash key Indexing
- 56. ID Date Total Hash key Range key Composite primary key Indexing
- 57. ID Date Total Hash key Range key Secondary range key Indexing
- 58. Programming DynamoDB. Small but perfectly formed API. CreateTable UpdateTable DeleteTable DescribeTable ListTables PutItem GetItem UpdateItem DeleteItem BatchGetItem BatchWriteItem Query Scan Manage tables Query specific items OR scan the full table “Select”, “insert”, “update” items Bulk select or update (max 1MB)
- 59. Query patterns Retrieve all items by hash key. Range key conditions: ==, <, >, >=, <=, begins with, between. Counts. Top and bottom n values. Paged responses.
- 60. 500,000 WRITES PER SECOND DURING SUPER BOWL
- 61. Amazon DynamoDB: who is succeeding with it?
- 62. Option 2.3: Managed datawarehouse database
- 63. OLTP <-> OLAP SELECT ProductID, Name FROM Products Where ProductID = 1234; SELECT ProductID, count(*) FROM Page_Hits WHERE hour in (12,13) GROUP BY ProductID
- 64. Transactional Processing • Global context – Daily revenue report • Throughput • Full table scans • Sequential IO • Disk Transfer rates Analytical Processing • Transactional context – Get order total • Latency • Indexed access • Random IO • Disk Seek times OLTP <-> OLAP
- 65. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service Amazon Redshift
- 66. Fast and powerful Parallelize and Distribute Everything Dramatically Reduce I/O Direct-attached storage Large data block sizes Column data store Data compression Zone maps MPP Load Query Resize Backup Restore
- 67. Fully Managed Protect Operations Simplify Provisioning Redshift data is always encrypted Continuously backed up to S3 Automatic node recovery Transparent disk failure Create a cluster in minutes Automatic OS and software patching Scale up to 1.6PB with a few clicks and no downtime
- 68. Amazon Redshift architecture 10 GigE (HPC) Ingestion Backup Restore JDBC/ODBC
- 69. Focus on your application
- 70. Best of both worlds: Use both SQL and NoSQL models in one app
- 71. More on Amazon Redshift? 03:15pm to 03:45pm Introducing the Amazon Redshift data warehouse Room Zero Speaker: Steffen Krause, Amazon