Azure Cosmos DB vs Redis

Overview

Redis

Stacks61.9K

Followers46.5K

Votes3.9K

GitHub Stars42

Forks6

Azure Cosmos DB

Stacks594

Followers1.1K

Votes130

Azure Cosmos DB vs Redis: What are the differences?

Azure Cosmos DB and Redis are both widely used distributed databases. Let's discuss the key differences between Azure Cosmos DB and Redis:

Database Model: Azure Cosmos DB is a document-oriented database that provides a schema-less data model. It allows you to store and query JSON documents natively. On the other hand, Redis is an in-memory data structure store that supports various data structures such as strings, lists, sets, hashes, and more. It is primarily used as a key-value store.
Scalability and Global Distribution: Azure Cosmos DB offers global distribution and scalable performance out of the box. It ensures low latency access to data from any region around the world and allows you to scale both read and write throughput independently. Redis also provides scalability, but it requires additional configuration and setup to achieve global distribution.
Data Persistence: Azure Cosmos DB offers multiple levels of data consistency, including strong consistency, bounded staleness, session consistency, and eventual consistency. It persists data durably across multiple Azure regions. In contrast, Redis is an in-memory database by default, and you need to configure it for persistence by periodically saving the data to disk or using replication.
Querying Capabilities: Azure Cosmos DB provides a SQL-like query language called SQL API, which allows complex queries on JSON documents. It also supports other APIs like Gremlin (graph database), MongoDB, Cassandra, and Azure Table Storage API. Redis, on the other hand, primarily supports simple key-based operations and does not have built-in support for complex querying.
TTL (Time-to-Live) and Expiry: Azure Cosmos DB allows you to set a time-to-live (TTL) for individual documents, so they automatically expire and get deleted after a specific duration. Redis also supports TTL, but it is more commonly used for setting expiry on individual keys rather than entire documents.
Data Replication and High Availability: Azure Cosmos DB provides automatic multi-region replication to ensure high availability and fault tolerance. It replicates data across multiple regions and provides automatic failover in case of region-wide failures. Redis supports replication as well but requires manual configuration and set up for high availability scenarios.

In summary, choose Azure Cosmos DB if you need a globally distributed, document-oriented database with strong querying capabilities and automatic replication. Choose Redis if you need an in-memory data store with support for various data structures and manual replication setup.

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Manual

Detailed Comparison

Redis	Azure Cosmos DB
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.	Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
-	Fully managed with 99.99% Availability SLA;Elastically and highly scalable (both throughput and storage);Predictable low latency: <10ms @ P99 reads and <15ms @ P99 fully-indexed writes;Globally distributed with multi-region replication;Rich SQL queries over schema-agnostic automatic indexing;JavaScript language integrated multi-record ACID transactions with snapshot isolation;Well-defined tunable consistency models: Strong, Bounded Staleness, Session, and Eventual
Statistics
GitHub Stars 42	GitHub Stars -
GitHub Forks 6	GitHub Forks -
Stacks 61.9K	Stacks 594
Followers 46.5K	Followers 1.1K
Votes 3.9K	Votes 130
Pros & Cons
Pros 888 Performance 542 Super fast 514 Ease of use 444 In-memory cache 324 Advanced key-value cache Cons 15 Cannot query objects directly 3 No secondary indexes for non-numeric data types 1 No WAL	Pros 28 Best-of-breed NoSQL features 22 High scalability 15 Globally distributed 14 Automatic indexing over flexible json data model 10 Tunable consistency Cons 18 Pricing 4 Poor No SQL query support
Integrations
No integrations available	Azure Machine Learning MongoDB Hadoop Java Azure Functions Azure Container Service Azure Storage Azure Websites Apache Spark Python

What are some alternatives to Redis, Azure Cosmos DB?

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

Google Cloud Bigtable

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Related Comparisons

Azure Cosmos DB vs Redis: What are the differences?

Azure Cosmos DB and Redis are both widely used distributed databases. Let's discuss the key differences between Azure Cosmos DB and Redis:

Database Model: Azure Cosmos DB is a document-oriented database that provides a schema-less data model. It allows you to store and query JSON documents natively. On the other hand, Redis is an in-memory data structure store that supports various data structures such as strings, lists, sets, hashes, and more. It is primarily used as a key-value store.
Scalability and Global Distribution: Azure Cosmos DB offers global distribution and scalable performance out of the box. It ensures low latency access to data from any region around the world and allows you to scale both read and write throughput independently. Redis also provides scalability, but it requires additional configuration and setup to achieve global distribution.
Data Persistence: Azure Cosmos DB offers multiple levels of data consistency, including strong consistency, bounded staleness, session consistency, and eventual consistency. It persists data durably across multiple Azure regions. In contrast, Redis is an in-memory database by default, and you need to configure it for persistence by periodically saving the data to disk or using replication.
Querying Capabilities: Azure Cosmos DB provides a SQL-like query language called SQL API, which allows complex queries on JSON documents. It also supports other APIs like Gremlin (graph database), MongoDB, Cassandra, and Azure Table Storage API. Redis, on the other hand, primarily supports simple key-based operations and does not have built-in support for complex querying.
TTL (Time-to-Live) and Expiry: Azure Cosmos DB allows you to set a time-to-live (TTL) for individual documents, so they automatically expire and get deleted after a specific duration. Redis also supports TTL, but it is more commonly used for setting expiry on individual keys rather than entire documents.
Data Replication and High Availability: Azure Cosmos DB provides automatic multi-region replication to ensure high availability and fault tolerance. It replicates data across multiple regions and provides automatic failover in case of region-wide failures. Redis supports replication as well but requires manual configuration and set up for high availability scenarios.

Azure Cosmos DB vs Redis

Overview