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In Microsoft Build 2017 event, I came across CosmosDB Table API. It looks like Azure Table Storage.
Does it mean Microsoft is going to stop supporting Azure Table Storage eventually?
Now, Document Db is no more. It has been converted to CosmosDB now.
Also, the major problem with Table Storage is backup. Which has been resolved in CosmosDB Table API.
Also, pricing strategy for Table API is Throughput-based whereas for Table Storage is Storage-based.
So is Table Storage still a good bet for high volume applications?
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The Table API provides the same query functionality as Azure Table storage. Azure Cosmos DB also supports sorting, aggregates, geospatial query, hierarchy, and a wide range of built-in functions. For more information, see SQL queries.
What is a benefit of the Azure Cosmos DB Table API as compared to Azure Table storage? Multi-master support for Azure Cosmos DB is now available in all public regions. Azure CosmosDB table API is a key-value storage hosted in the cloud. It's a part of Azure Cosmos DB, that is Microsoft's multi-model database.
Azure Table Storage supports a single region with an optional read-only secondary region for availability. Cosmos DB supports distribution from 1 to more than 30 regions with automatic failovers worldwide. You can easily manage this from the Azure portal and define the failover behavior.
Cassandra API is wire protocol compatible with the Apache Cassandra. You should consider Cassandra API if you want to benefit the elasticity and fully managed nature of Azure Cosmos DB and still use most of the native Apache Cassandra features, tools, and ecosystem.
As Peter responded, DocumentDB now is part of Cosmos DB, it is one of the many Data Models the new service has available including MongoDB API, Premium Tables API, and Gremlin Graph API.
They all have the same global distribution capabilities and consistency levels.
Now, going to your Tables question, both services have a different scenario and pricing model.
While Azure Storage Tables is aimed at high capacity on a single region (optional secondary read only region but no failover), indexing by PK/RK and storage-optimized pricing; Azure Cosmos DB Tables aims for high throughput (single-digit millisecond latency), global distribution (multiple failover), SLA-backed predictive performance with automatic indexing of each attribute/property and a pricing model focused on throughput.
Depending on your scenario is the service you might want to use, Azure Storage Tables is still a great solution, but if, for example, you need global distribution, Cosmos DB Tables is a best suited service.
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