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Azure Cosmos DB VS MarkLogic Server

Compare Azure Cosmos DB VS MarkLogic Server and see what are their differences

Azure Cosmos DB logo Azure Cosmos DB

NoSQL JSON database for rapid, iterative app development.

MarkLogic Server logo MarkLogic Server

MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.
  • Azure Cosmos DB Landing page
    Landing page //
    2023-03-16
  • MarkLogic Server Landing page
    Landing page //
    2023-07-27

Azure Cosmos DB features and specs

  • Global Distribution
    Azure Cosmos DB allows for the distribution of data across multiple global regions, enhancing availability and delivering low-latency access to data for users around the world.
  • Multi-Model Support
    It supports multiple data models including document, graph, key-value, and column-family APIs, making it versatile for a variety of applications and use cases.
  • Automatic Scaling
    The database automatically scales up and down to meet the demands of application traffic, helping to manage workloads efficiently without manual intervention.
  • High Throughput and Low Latency
    Cosmos DB offers high performance with single-digit millisecond read and write latencies, ensuring fast access to data for applications.
  • Comprehensive SLAs
    Azure Cosmos DB provides industry-leading SLAs covering availability, throughput, consistency, and latency, offering strong guarantees for customers.
  • Integrated Security
    It includes robust security features such as SSL/TLS encryption, role-based access control, and integration with Azure Active Directory for secure data management.

Possible disadvantages of Azure Cosmos DB

  • Cost
    Azure Cosmos DB can be expensive, especially for high-throughput workloads and global distribution scenarios. Its pricing model based on provisioned throughput (RU/s) can add up quickly.
  • Complexity
    Managing and optimizing Cosmos DB can be complex, requiring a deep understanding of its configuration settings, partitioning strategies, and indexing to achieve optimal performance.
  • Vendor Lock-In
    As a proprietary service, using Cosmos DB tightly couples your application to Azure. This can make it difficult to migrate to other database solutions or cloud providers in the future.
  • Consistency Models
    Azure Cosmos DB supports multiple consistency levels which can introduce complexity in designing applications. Developers need to understand and choose the appropriate consistency level for their specific use case.
  • Limited Native Analytics
    Cosmos DB does not have built-in advanced analytics capabilities. Integrating with other services like Azure Synapse or Databricks may be necessary for sophisticated data analytics and reporting.

MarkLogic Server features and specs

  • Multi-Model Database
    MarkLogic Server is a multi-model database that supports documents, graphs, and relational data, allowing for versatility in storing and managing various data types.
  • Enterprise Features
    Includes enterprise-grade features such as ACID transactions, built-in search capability, scalability, high availability, and disaster recovery.
  • Security
    Offers advanced security controls including role-based access, encryption, and auditing, which are crucial for handling sensitive and regulated data.
  • Integrated Search
    Provides powerful search capabilities out-of-the-box, which can index and search text, structure, and metadata across all data types efficiently.
  • Data Integration
    Facilitates data integration from multiple sources, supporting seamless interoperability and operational data hubs, which is beneficial for complex data environments.

Possible disadvantages of MarkLogic Server

  • Complexity and Learning Curve
    While rich in features, it may have a steep learning curve for new users, which could lead to a longer setup and training time.
  • Cost
    Can be expensive, especially for smaller organizations, as it comes with licensing costs typical of enterprise-grade software.
  • Vendor Lock-in
    Using a proprietary database like MarkLogic can create risks of vendor lock-in, potentially complicating data migrations to other platforms if needed.
  • Limited Community Support
    Compared to open-source alternatives, there might be less community support available, which can be a drawback for troubleshooting or finding resources.
  • Performance Overhead
    Due to its extensive feature set, there can be performance overhead, requiring careful management and optimal configuration to achieve desired performance.

Azure Cosmos DB videos

Azure Cosmos DB: Comprehensive Overview

More videos:

  • Review - Azure Friday | Azure Cosmos DB with Scott Hanselman
  • Tutorial - Azure Cosmos DB Tutorial | Globally distributed NoSQL database

MarkLogic Server videos

No MarkLogic Server videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Azure Cosmos DB and MarkLogic Server)
Databases
77 77%
23% 23
NoSQL Databases
92 92%
8% 8
Relational Databases
40 40%
60% 60
Graph Databases
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Azure Cosmos DB seems to be more popular. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure Cosmos DB mentions (9)

  • Blazor server app, deployment options
    If you are writing the code maybe consider learning Cosmos DB it’s pretty easy to work with and there is a free tier. Also in my experience it’s much faster than a SQL database. Source: almost 2 years ago
  • Infrastructure as code (IaC) for Java-based apps on Azure
    Sometimes you don’t need an entire Java-based microservice. You can build serverless APIs with the help of Azure Functions. For example, Azure functions have a bunch of built-in connectors like Azure Event Hubs to process event-driven Java code and send the data to Azure Cosmos DB in real-time. FedEx and UBS projects are great examples of real-time, event-driven Java. I also recommend you to go through 👉 Code,... - Source: dev.to / over 2 years ago
  • Deploying a Mostly Serverless Website on GCP
    When debating the database solution for our application we were really seeking for a scalable serverless database that wouldn’t bill us for idle time. Options like AWS Athena, AWS Aurora Serverless, and Azure Cosmos DB immediately came to mind. We believed that GCP would have a comparable service, yet we could not find one. Even after consulting the GCP cloud service comparison documentation we were still unable... - Source: dev.to / almost 3 years ago
  • Which DB to use for API published on Azure?
    If you are looking for one to start with; you can try Cosmos: https://azure.microsoft.com/en-us/services/cosmos-db/. Source: about 3 years ago
  • Basic Setup for Azure Cosmos DB and Example Node App
    I have had an opportunity to work on a project that uses Azure Cosmos DB with the MongDB API as the backend database. I wanted to spend a little more time on my own understanding how to perform basic setup and a simple set of CRUD operations from a Node application, as well as construct an easy-to-follow procedure for other developers. - Source: dev.to / about 3 years ago
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MarkLogic Server mentions (0)

We have not tracked any mentions of MarkLogic Server yet. Tracking of MarkLogic Server recommendations started around Apr 2022.

What are some alternatives?

When comparing Azure Cosmos DB and MarkLogic Server, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Datomic - The fully transactional, cloud-ready, distributed database

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

PlanetScale - The last database you'll ever need. Go from idea to IPO.