# LAMBDA Vs KAPPA

1\) <https://towardsdatascience.com/a-brief-introduction-to-two-data-processing-architectures-lambda-and-kappa-for-big-data-4f35c28005bb> ++++++++++++++++

![](/files/-Ld8C1m12FeYuAXFIO_O)

```
Query = λ (Complete data) = λ (live streaming data) * λ (Stored data)
```

**Lambda architecture can be deployed for those data processing enterprise models where:**

* User queries are required to be served on ad-hoc basis using the immutable data storage.
* Quick responses are required and system should be capable of handling various updates in the form of new data streams.
* None of the stored records shall be erased and it should allow addition of updates and new data to the database.

Companies like Twitter, Netflix, and Yahoo are using this architecture to meet the quality of service standards.

&#x20;                                 **KAPPA ARCHITECTURE**

![](/files/-Ld8CivXKH_vrrFyo-Gi)

```
Query = K (New Data) = K (Live streaming data)
```

**Kappa architecture can be deployed for those data processing enterprise models where:**

* Multiple data events or queries are logged in a queue to be catered against a distributed file system storage or history.
* The order of the events and queries is not predetermined. Stream processing platforms can interact with database at any time.
* It is resilient and highly available as handling Terabytes of storage is required for each node of the system to support replication.


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