Compare Azure Blob Storage vs. Data Lake
Capacity, security features and pricing are just a few of the many factors to consider when organizations compare Azure Blob Storage and Data Lake.
Storage administrators who use Azure can choose from a range of cloud storage services. Two of those services -- Azure Blob Storage and Azure Data Lake -- offer distinct features and capabilities but also share some key similarities.
Azure Blob Storage is one of the most common Azure storage types. It's an object storage service for workloads that need high-capacity storage. Azure Data Lake is a storage service intended primarily for big data analytics workloads.
Top uses and features
Azure Blob Storage and Data Lake are well suited to specific situations and uses.
For example, Blob -- which is shorthand for binary large object -- is ideal for large amounts of unstructured data, such as text, videos, photos, application back-end data and backup data. It's a general-purpose object store for unstructured data in a single hierarchy and a flat namespace.
Common uses for Azure Blob Storage include the following:
- Storing files for distributed access, such as installation or upgrades.
- Streaming video and audio.
- Storing backups for DR and archiving.
- Storing binary data, such as application back-end files and general-purpose data.
Azure Data Lake storage is currently separated into Gen1 and Gen2 options. Microsoft will retire Data Lake Gen1 storage in February 2024, and all customers using it must migrate to Gen2 before this date.
Azure Data Lake Gen1 is a storage service that's optimized for big data analytics workloads. Its hierarchical file system can store machine learning data, including log files, as well as interactive streaming analytics. It is performance-tuned to run large-scale analytics systems that require massive throughput and bandwidth to query and analyze large amounts of data.
Azure Data Lake Gen2 converges the features and capabilities of Data Lake Gen1 with Blob Storage. It inherits the file system semantics, file-level security and scaling features of Gen1 and builds them on Blob Storage. This results in a low-cost, tiered-access, high-security and high availability big data storage option.
Benefits and challenges of Azure Blob vs. Data Lake storage
Azure blobs are a durable storage option, with appropriate redundancy options to keep data safe. All data is encrypted, and there is fine-grained access control. Azure blobs are also massively scalable for text and binary data.
One challenge of Azure blobs is when customers use it, they can incur lots of data transfer charges. Along with the typical data transfer read/write charges at the various tiers -- Premium, Hot, Cool and Archive -- there are iterative read/write operation charges, indexing charges, SSH FTP transfers, fees for data transfers for georeplicated data and more. Each transfer type may only cost fractions of cents, but when doing hundreds of thousands of transactions, these costs can add up quickly.
Azure Data Lake enables users to store and analyze petabytes (PB) of data quickly and efficiently. It centralizes data storage, encrypts all data and offers role-based access control. Because Data Lake storage is highly customizable, it is economical. Users can independently scale storage and computing services and use object-level tiering to optimize costs.
However, there are numerous known issues with Gen2, including one with Blob storage APIs that prevents some REST APIs from working properly.
Both Azure Blob Storage and Data Lake offer pay-as-you-go pricing based on the volume of data stored per month, the quantity and types of operations performed, and any data redundancy options selected.
Users can also choose a Reserved Capacity option in increments of 100 TB and 1 PB for one-year and three-year commitments. This is ideal for companies with relatively stable storage needs or for those that access archives and backups infrequently.
Blob Storage pricing varies based on tiers: Premium, Hot, Cool and Archive. The Premium option is best for I/O-intensive workloads that require low and consistent storage latency. Storage pricing increases from Archive to Cool to Hot to Premium, while transaction pricing decreases through the same progression -- for example, Archive transactions cost more than Premium ones.
Organizations that use multiple Azure products and services should use the Azure pricing calculator to ensure the best possible pricing.