DynamoDB Backup and Restore provides fully automated on-demand backup, restore, and point-in-time recovery for data protection and archiving.
On-demand backup allows the creation of full backups of DynamoDB table for data archiving, helping you meet corporate and governmental regulatory requirements.
Point-in-time recovery (PITR) provides continuous backups of your DynamoDB table data. When enabled, DynamoDB maintains incremental backups of your table for the last 35 days until you explicitly turn it off.
DynamoDB on-demand backup helps create full backups of the tables for long-term retention, and archiving for regulatory compliance needs.
Backup and restore actions run with no impact on table performance or availability.
Backups are preserved regardless of table deletion and retained until they are explicitly deleted.
On-demand backups are cataloged, and discoverable.
On-demand backups can be created using
can be used to backup and restore DynamoDB tables.
DynamoDB on-demand backups cannot be copied to a different account or Region.
DynamoDB Global Tables is a new multi-master, cross-region replication capability of DynamoDB to support data access locality and regional fault tolerance for database workloads.
DynamoDB Streams provides a time-ordered sequence of item-level changes made to data in a table.
DynamoDB Triggers (just like database triggers) are a feature that allows the execution of custom actions based on item-level updates on a table.
DynamoDB Accelerator – DAX is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from ms to µs – even at millions of requests per second.
DynamoDB Secondary indexes on a table allow efficient access to data with attributes other than the primary key.
Global secondary index – an index with a partition key and a sort key that can be different from those on the base table.
Local secondary index – an index that has the same partition key as the base table, but a different sort key.
DynamoDB Time to Live (TTL) enables a per-item timestamp to determine when an item is no longer needed.
After the date and time of the specified timestamp, DynamoDB deletes the item from the table without consuming any write throughput.
DynamoDB TTL is provided at no extra cost and can help reduce data storage by retaining only required data.
Items that are deleted from the table are also removed from any local secondary index and global secondary index in the same way as a DeleteItem operation.
Expired items get removed from the table and indexes within about 48 hours.
DynamoDB Stream tracks the delete operation as a system delete and not a regular delete.
TTL is useful if the stored items lose relevance after a specific time. for e.g.
Remove user or sensor data after a year of inactivity in an application
Archive expired items to an S3 data lake via DynamoDB Streams and AWS Lambda.
Retain sensitive data for a certain amount of time according to contractual or regulatory obligations.
DynamoDB Cross-region Replication
DynamoDB cross-region replication allows identical copies (called replicas) of a DynamoDB table (called master table) to be maintained in one or more AWS regions.
Writes to the table will be automatically propagated to all replicas.
Cross-region replication currently supports a single master mode. A single master has one master table and one or more replica tables.
Read replicas are updated asynchronously as DynamoDB acknowledges a write operation as successful once it has been accepted by the master table. The write will then be propagated to each replica with a slight delay.
Cross-region replication can be helpful in scenarios
Efficient disaster recovery, in case a data center failure occurs.
Faster reads, for customers in multiple regions by delivering data faster by reading a DynamoDB table from the closest AWS data center.
Easier traffic management, to distribute the read workload across tables and thereby consume less read capacity in the master table.
Easy regional migration, by promoting a read replica to master
Live data migration, to replicate data and when the tables are in sync, switch the application to write to the destination region
Cross-region replication costing depends on
Provisioned throughput (Writes and Reads)
Storage for the replica tables.
Data Transfer across regions
Reading data from DynamoDB Streams to keep the tables in sync.
Cost of EC2 instances provisioned, depending upon the instance types and region, to host the replication process.
NOTE : Cross Region replication on DynamoDB was performed defining AWS Data Pipeline job which used EMR internally to transfer data before the DynamoDB streams and out-of-box cross-region replication support.
DynamoDB Global Tables
DynamoDB Global Tables is a multi-master, active-active, cross-region replication capability of DynamoDB to support data access locality and regional fault tolerance for database workloads.
Applications can now perform reads and writes to DynamoDB in AWS regions around the world, with changes in any region propagated to every region where a table is replicated.
Global Tables help in building applications to advantage of data locality to reduce overall latency.
Global Tables supports eventual consistency & strong consistency for same region reads, but only eventual consistency for cross-region reads.
Global Tables replicates data among regions within a single AWS account and currently does not support cross-account access.
Global Tables uses the Last Write Wins approach for conflict resolution.
Global Tables requires DynamoDB streams enabled with New and Old image settings.
DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second.
DAX is intended for high-performance read applications. As a write-through cache, DAX writes directly so that the writes are immediately reflected in the item cache.
DAX as a managed service handles the cache invalidation, data population, or cluster management.
DAX provides API-compatible with DynamoDB. Therefore, it requires only minimal functional changes to use with an existing application.
DAX saves costs by reducing the read load (RCU) on DynamoDB.
DAX helps prevent hot partitions.
DAX only supports eventual consistency, and strong consistency requests are passed-through to DynamoDB.
DAX is fault-tolerant and scalable.
DAX cluster has a primary node and zero or more read-replica nodes. Upon a failure for a primary node, DAX will automatically failover and elect a new primary. For scaling, add or remove read replicas.
DAX supports server-side encryption.
DAX also supports encryption in transit, ensuring that all requests and responses between the application and the cluster are encrypted by TLS, and connections to the cluster can be authenticated by verification of a cluster x509 certificate
VPC endpoints for DynamoDB improve privacy and security, especially those dealing with sensitive workloads with compliance and audit requirements, by enabling private access to DynamoDB from within a VPC without the need for an internet gateway or NAT gateway.
VPC endpoints for DynamoDB support IAM policies to simplify DynamoDB access control, where access can be restricted to a specific VPC endpoint.
VPC endpoints can be created only for Amazon DynamoDB tables in the same AWS Region as the VPC
DynamoDB Streams cannot be accessed using VPC endpoints for DynamoDB.
AWS Certification Exam Practice Questions
Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
Open to further feedback, discussion and correction.
What are the services supported by VPC endpoints, using Gateway endpoint type? Choose 2 answers
A company has setup an application in AWS that interacts with DynamoDB. DynamoDB is currently responding in milliseconds, but the application response guidelines require it to respond within microseconds. How can the performance of DynamoDB be further improved? [SAA-C01]