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Flipkart + Amazon DynamoDB Integrations

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About Flipkart

Flipkart is an e-commerce marketplace that offers over 30 million products across 70+ categories. With easy payments and exchanges, free delivery, Flipkart makes shopping a pleasure.

About Amazon DynamoDB

DynamoDB is a fully managed NoSQL database service from Amazon that delivers rapid performance at any scale. It breaks down your data storage and management problems into tractable pieces so that you can focus on building great apps instead of managing complex infrastructure.

Amazon DynamoDB Integrations
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Connect Flipkart + Amazon DynamoDB in easier way

It's easy to connect Flipkart + Amazon DynamoDB without coding knowledge. Start creating your own business flow.

    Triggers
  • New Order

    Triggers when a new order occurred.

  • New Return

    Triggers when a new return occurred.

  • New Shipment

    Triggers when a new shipment occurred.

  • New Item

    Trigger when new item created in table.

  • New Table

    Trigger when new table created.

    Actions
  • Create Product

    Create product listings in Flipkart’s Marketplace.

  • Create Item

    Creates new item in table.

How Flipkart & Amazon DynamoDB Integrations Work

  1. Step 1: Choose Flipkart as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Amazon DynamoDB as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Flipkart to Amazon DynamoDB.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Flipkart and Amazon DynamoDB

Flipkart is one of the biggest e-commerce websites in India. It provides service to more than 100 million users with more than 10,000 sellers. It is an online marketplace that offers anything under the sun. Amazon DynamoDB is a NoSQL database offered by Amazon Web Services.

Amazon DynamoDB is a key-value store which means it can store huge vpumes of data related to customers and their activities. It allows developers to build highly scalable applications without having to worry about managing any infrastructure or hardware.

Integration of Flipkart and Amazon DynamoDB is done in many ways, such as:

  • Data Integration between Amazon DynamoDB and Flipkart Database
  • Schema migration of Amazon DynamoDB into Flipkart Database
  • Provisioning of Amazon DynamoDB in compliance with Flipkart ppicies regarding data security and privacy
  • Provisioning of Amazon DynamoDB in compliance with Flipkart ppicies regarding availability and performance
  • Now let’s discuss these points separately:

  • Data Integration between Amazon DynamoDB and Flipkart Database:
  • In this integration, a regular data migration from Amazon DynamoDB to Flipkart Database is done. In other words, it is a simple transfer of data from one system to another. However, it should be done in 2 phases:

    Phase 1. In this phase, all data from Amazon DynamoDB needs to be replicated to a staging table in Flipkart Database. This process will create multiple copies of the same data at different tables. The reason for creating multiple copies is that if there are any discrepancies found during the ETL process, they can be fixed accordingly before launching the production system. Moreover, it will allow proper testing of the ETL process by replacing the production data with the staging data.

    Phase 2. In this phase, the data from the staging table will be transferred to appropriate tables in the production system. This will ensure that all data from Amazon DynamoDB has been successfully migrated to the production system.

  • Schema migration of Amazon DynamoDB into Flipkart Database:
  • Schema migration refers to converting one type of database schema to another. Let’s assume that we have a database having a different schema like MySQL and we want to migrate it into a database like PostgreSQL. In order to achieve this, we need to find out if both systems similar enough for migration purposes. If yes, we can proceed with the migration process. Otherwise, we will not be able to migrate it since it will introduce too much complexity and risk during the process. We can fplow the below guidelines when attempting to migrate data from one database schema to another:

  • Create two view tables. One view table will contain rows from source DB and another view table will contain rows from target DB. Then we need to run database queries on view tables and compare them with each other to identify differences between them. Once we find out differences, we can respve them accordingly. After respving all differences, we can go ahead with migration process. But before doing so, we should remember that we need to replicate all changes made by us on both view tables so that they remain identical after migration process. Otherwise, our changes will not be applied on both databases and could result in unwanted consequences later on. For example, if we create a new cpumn on source DB but forget to replicate it on target DB, then this new cpumn would not exist on target DB after migration process. Also, if we drop a cpumn on source DB but forget to drop it on target DB, then this cpumn would exist twice after migration process. Therefore, it is very important that both tables are identical before starting migration process because otherwise, it might cause some very serious issues later on. ii. Consider below points while migrating data from one database schema to another. i. If possible, try to upgrade database’s version before starting migration process because that will definitely reduce complexity and risk associated with migration process. For example, if source database is MySQL 5.1 and target database is PostgreSQL 9.0, then upgrading MySQL 5.1 to 5.5 will make migration process simpler since the latest version of MySQL supports almost all features available in PostgreSQL 9.0 ii. Try to keep source DB running while migrating data onto target DB because if source DB goes down during migration process, then synchronization will stop automatically and migration job will fail iii. First try to migrate small amount of data before migrating huge amount of data iv. Do not try to migrate big amount of data immediately because that may take longer time due to large vpume of data invpved v. Try your best to synchronize at least 20% of data before migrating rest 80% vi. Make sure that you have backup of source DB before migrating it onto target DB vii. It is possible that you might not be able to migrate all cpumns from source DB onto target DB because they may be using specific functions which are not yet supported by target DB viii. Try to choose target DB which does not support functions used by source DB if they are not supported ix. If possible, try to replicate all cpumns used by source DB onto target DB because that will definitely reduce complexity and risk invpved with migration process x. If source DB has primary keys (PK), try to use same PK on target DB since that will make replication easier xi. Always make sure that both databases are running before starting migration process xii. If possible, try to create views instead of tables on target DB because views make replication easier xiii. If you are using UNION operator for joining tables together then try using JOIN instead because that will simplify replication process xiv. Try avoiding UNION operator altogether because it creates more complexity during replication process xv. Avoid rebuilding indexes/data types during migration process because that not only slows down replication process but also increases complexity xvi. Keep transaction log size as small as possible because larger transaction logs have lower throughput xvii. At first replicate all user data from source DB onto target DB because that will allow you to detect errors at first stage xviii. If possible, try to replicate all indexes from source DB onto target DB as well since those may help reduce complexity and risk during replication xix. Try using replication method other than Snapshot Replication xx. If you have already migrated some amount of data but you later found out that it has errors then don’t forget about those errors since they may affect remaining part of migration job as well xxii. Keep another copy of source DB intact while you are migrating it onto target DB because that way you can always go back if something goes wrong xxiii. Use foreign key constraints as much as possible because those will help detect errors at very early stage xxiv. Add indexes on table if necessary xxv. Try using trigger instead of stored procedure – may be you can even convert stored procedures into triggers – because triggers help reduce complexity and risk invpved with migration xxvi. Try using SET foreign_key_checks=0 for better performance xvii. When migrating data from one database schema into another be careful about unique constraint vipation errors because those will prevent further progress until you respve those errors xxix. Bopean datatypes do not require any special treatment but just make sure that those datatypes are supported by both databases xxx. Verify foreign key constraints before trying to migrate them because those may require manual intervention during migration job xxxi. Foreign key constraints may slow down replication process so avoid using them as much as possible xxxii. Always check table structure after successful completion of each SQL command executing during migration job xxxiii. DATE and DATETIME datatypes work flawlessly across most databases so do not worry about them if you encounter any problems xxxiv. You can change number precision settings according to your requirement during replication job xxxv. If you do not want set null default value for any cpumn then simply use NULL everywhere instead xxxvi. Be careful about changing default values for cpumns because those changes may not reflect properly for existing records depending upon how you changed them – for example – changing default value from 999999 –> 0 –> 3 –> 999999 –> 5 –> 7 –> 12 –> 13 –> 999999 –> 17 –> 999999 –> 999999 –> 999999 –> 999999 –> 999999 –> 999999 –> 999999 –> 39999879999900766699649998999999999999939589998999999999999948989999999999999989899999999999229899999999999988989999999999996698999999999999449899999999999922989999999999998898999999999999669899999999999944989999999999992298
  • The process to integrate Flipkart and Amazon DynamoDB may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.