Choosing an appropriate consistency model is an essential step while designing and implementing native applications using Microsoft Azure Cosmos DB and the path to attaining this is covered under the DP-420 exam. The selection of a consistency model has a substantial impact on the availability, latency, throughput, and data consistency of your application. In the following sections, we’ll explore the various consistency models provided by Azure Cosmos DB.
1. Strong Consistency
The strong consistency model guarantees linearizing access to your data. In simpler terms, it means that reads are guaranteed to return the most recent committed write. In this model, there is no chance of reading outdated data, hence ensuring the highest level of consistency.
2. Bounded Staleness Consistency
Bound staleness consistency guarantees that reads might lag behind writes by ‘k’ prefixes (K could mean time or number of operations). Bounded staleness offers a compromise between performance and guaranteed staleness of data. It is suitable for applications where precise data is not a matter of utmost urgency, and minimal delay can be tolerated.
3. Session Consistency
Session consistency guarantees monotonic reads, monotonic writes, and read-your-own-writes within a single session. This is particularly beneficial for scenarios where an application needs to guarantee that a sequence or ‘session’ of operations always reads and writes its own data.
4. Consistent Prefix Consistency
Consistent prefix consistency guarantees that reads never see out-of-order writes. If writes were performed in the order `A-B-C`, then a client sees either `A`, `A-B`, or `A-B-C`, but never out-of-order combinations like `A-C`.
5. Eventual Consistency
Eventual consistency provides the weakest consistency, where there is a probable delay between a write operation and its visibility to a reader. There are no guarantees about the order in which data will be read relative to the order in which data was written.
Comparing Consistency Models
Below is a comparison table showing the strengths and weaknesses of each consistency model.
| Consistency Model | Availability and Latency | Throughput | Consistency |
|---|---|---|---|
| Strong | Lowest | Lowest | Highest |
| Bounded Staleness | Moderate | Moderate | High |
| Session | High | High | Moderate |
| Consistent Prefix | Higher | Higher | Lower |
| Eventual | Highest | Highest | Lowest |
Conclusion
The choice of consistency models basically depends on the specific needs of your application. While strong consistency offers the highest level of data accuracy, it can have an impact on the availability, latency and throughput. On the other hand, eventual consistency may provide more speed and availability at the cost of more recent data. Hence, developers should properly consider the working environment and the nature of the application before opting for a consistency model. For example, a banking app may need to choose strong consistency to ensure the most accurate data, whereas a blogging platform would choose eventual consistency to prioritize availability and performance. Remember, there is no ‘One-Size-Fits-All’ model – picking the right consistency model for your application is an intricate balance between data accuracy and performance.
Remember that Azure Cosmos DB provides flexibility to choose different consistency models on a per request level. As a developer, architect or data engineer studying for DP-420 exam, understanding and choosing the right consistency model for your use-case is a significant knowledge milestone.
Practice Test
True or False: The eventual consistency model offers the lowest latency and highest availability in Azure Cosmos DB’s consistency models.
- True
Answer: True
Explanation: The eventual consistency model provides the lowest latency and highest availability, but there may be a delay in propagation of data updates.
Which consistency model in Azure Cosmos DB provides a balance between performance, availability and data consistency?
- A) Strong
- B) Bounded staleness
- C) Session
- D) Eventual
Answer: B) Bounded staleness
Explanation: Bounded staleness guarantees a specific lag between reads and writes, providing a balance between performance, availability, and data consistency.
In Azure Cosmos DB, the strong consistency model is the best choice for applications that require immediate consistency of data across all replicas.
- True
Answer: True
Explanation: Strong consistency provides immediate consistency and is ideal for applications where immediate consistency across all replicas is required.
Multiple choice: What consistency model ensures that once an update has been acknowledged, it can be read immediately from any replica?
- A) Session Consistency
- B) Strong Consistency
- C) Eventual Consistency
- D) Consistent Prefix
Answer: B) Strong Consistency
Explanation: Strong consistency is the strictest model in Azure Cosmos DB which ensures that once an update is acknowledged, it can be read immediately from any replica.
True or false: Session consistency guarantees that within a single session, a client never reads outdated data.
- True
Answer: True
Explanation: Session consistency provides a guarantee that within a single session, a client never reads outdated data, providing a balance between availability and consistency.
Which Azure Cosmos DB consistency model ensures the order of the operations?
- A) Consistent Prefix
- B) Session
- C) Strong
- D) Eventual
Answer: A) Consistent Prefix
Explanation: Consistent Prefix ensures that reads never see out-of-order writes which guarantees the order of operations.
True or False: Azure Cosmos DB supports five types of consistency models.
- True
Answer: True
Explanation: Azure Cosmos DB supports five consistency models: strong, bounded staleness, session, consistent prefix, and eventual.
Which consistency model in Azure Cosmos DB can impact availability during network partitions?
- A) Strong
- B) Eventual
- C) Session
- D) Bounded staleness
Answer: A) Strong
Explanation: Strong consistency model can impact availability during network partitions as it provides immediate consistency.
True or False: In session consistency, the order of the operations is not preserved.
- False
Answer: False
Explanation: Session consistency does preserve operation order within a single session.
Which consistency model in Azure Cosmos DB provides the highest latency?
- A) Strong
- B) Eventual
- C) Session
- D) Bounded staleness
Answer: A) Strong
Explanation: The strong consistency model provides the highest latency as it provides immediate consistency which can slow down operations.
True or False: Azure Cosmos DB automatically picks a consistency model for you.
- False
Answer: False
Explanation: You choose the default consistency model when you create an Azure Cosmos DB account.
In Azure Cosmos DB’s session consistency model, data is immediately consistent within a single session.
- True
Answer: True
Explanation: Session consistency ensures that reads are guaranteed to honor the consistency of writes within a single session.
Which Azure Cosmos DB consistency model is the default model?
- A) Session
- B) Strong
- C) Bounded staleness
- D) Eventual
Answer: A) Session
Explanation: By default, Azure Cosmos DB uses session consistency which provides consistent data within a single session.
True or False: Write operations in all the consistency models of Azure Cosmos DB are always consistent.
- True
Answer: True
Explanation: In all consistency models, write operations in Azure Cosmos DB are always strongly consistent.
Which consistency model promotes high availability at the expense of data consistency?
- A) Strong
- B) Eventual
- C) Session
- D) Bounded staleness
Answer: B) Eventual
Explanation: The eventual model promotes high availability even at the expense of data consistency, as it routes requests to any available replica.
Interview Questions
What is a consistency model in Microsoft Azure Cosmos DB?
A consistency model in Microsoft Azure Cosmos DB determines how changes are propagated to copies of data in the database. There are five consistency models in Azure Cosmos DB: Eventual, Consistent Prefix, Session, Bounded Staleness, and Strong.
What is the eventual consistency model in Azure Cosmos DB?
Eventual consistency is the model where replicas are allowed to diverge, and changes are propagated to all replicas eventually. This model provides the highest availability and lowest latency but does not guarantee immediate consistency.
When is the Strong consistency model considered appropriate in Azure Cosmos DB?
Strong consistency is considered appropriate when consistency requirements are demanding, mainly when an application cannot tolerate out-of-date or inconsistent data. It ensures linearizability, i.e., reads will always see the most recent committed write.
What type of consistency model does the session consistency offer in Cosmos DB?
Session consistency guarantees consistency within a single session, so reads are guaranteed to honor the consistent-prefix, monotonic reads, monotonic writes, read-your-own writes, and write follows read consistency levels within a session.
What is Bounded Staleness in Azure Cosmos DB’s consistency model?
Bounded Staleness guarantees a specific lag between reads and writes, allowing for some out-of-date reads but limiting how stale the data can be.
How does the Consistent Prefix model work in Azure Cosmos DB?
Consistent Prefix ensures that reads never see out-of-order writes. If writes were performed in the order A, B, C, then a client will never see C without seeing A and B.
How can you choose the consistency model in Azure Cosmos DB?
You can select a default consistency level for your Azure Cosmos account in the Azure portal, Azure CLI, Azure PowerShell, or one of the SDKs. This level can be overridden on a per-request basis.
Which consistency model provides the best performance in Cosmos DB?
The Eventual consistency model provides the lowest latency and highest availability, and thus the best performance, as it doesn’t require synchronization across replicas.
Which Azure Cosmos DB consistency model offers the strongest consistency?
The Strong consistency model offers the strongest consistency in Azure Cosmos DB.
Can you change the consistency level set at the account level in Azure Cosmos DB?
Yes, the consistency level set at the account level serves as the default for all requests, but it can be overridden on a per-request basis.
What is the primary trade-off to consider when choosing a consistency model in Azure Cosmos DB?
The primary trade-off when choosing a consistency model is between consistency and performance. Stronger consistency levels like Strong and Bounded Staleness have higher latencies and lower availability, while weaker consistencies like Eventual have lower latencies and higher availability.
What are monotonic reads and writes in Cosmos DB’s consistency model?
Monotonic reads ensure that once a client has read the data at a certain timestamp, any subsequent reads will not retrieve older data. Monotonic writes guarantee that writes by a client are ordered even if they are concurrently writing.
What is the impact of network latency on the consistency models in Azure Cosmos DB?
Stronger consistency levels like Strong and Bounded Staleness are more affected by network latency as they require synchronization between replicas. Weaker consistency levels like Eventual are less affected as they do not need immediate synchronization.
How does the consistency model in Azure Cosmos DB affect application development?
The choice of consistency model can influence how developers handle data updates, conflict resolution, and synchronization within the application. For some applications, using a weaker consistency level can simplify development by avoiding the need to manage conflicting updates.
How to handle conflicts in Azure Cosmos DB?
In Azure Cosmos DB, conflicts are handled automatically based on the specified conflict resolution policy. The policy can be set to either last writer wins based on a system or user-defined property or can be custom with a stored procedure.
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