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  1. Stackups
  2. Application & Data
  3. NoSQL Databases
  4. NOSQL Database As A Service
  5. Azure Cosmos DB vs MarkLogic

Azure Cosmos DB vs MarkLogic

OverviewComparisonAlternatives

Overview

Azure Cosmos DB
Azure Cosmos DB
Stacks594
Followers1.1K
Votes130
MarkLogic
MarkLogic
Stacks43
Followers71
Votes26

Azure Cosmos DB vs MarkLogic: What are the differences?

Azure Cosmos DB: A fully-managed, globally distributed NoSQL database service. 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; MarkLogic: Schema-agnostic Enterprise NoSQL database technology, coupled w/ powerful search & flexible application services. MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services.

Azure Cosmos DB belongs to "NoSQL Database as a Service" category of the tech stack, while MarkLogic can be primarily classified under "Databases".

Some of the features offered by Azure Cosmos DB are:

  • 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

On the other hand, MarkLogic provides the following key features:

  • Search and Query
  • ACID Transactions
  • High Availability and Disaster Recovery

"Best-of-breed NoSQL features" is the top reason why over 13 developers like Azure Cosmos DB, while over 3 developers mention "RDF Triples" as the leading cause for choosing MarkLogic.

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Detailed Comparison

Azure Cosmos DB
Azure Cosmos DB
MarkLogic
MarkLogic

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.

MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services.

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
Search and Query;ACID Transactions;High Availability and Disaster Recovery;Replication;Government-grade Security;Scalability and Elasticity;On-premise or Cloud Deployment;Hadoop for Storage and Compute;Semantics;Faster Time-to-Results
Statistics
Stacks
594
Stacks
43
Followers
1.1K
Followers
71
Votes
130
Votes
26
Pros & Cons
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
Pros
  • 5
    RDF Triples
  • 3
    Marklogic is absolutely stable and very fast
  • 3
    JSON
  • 3
    Enterprise
  • 3
    JavaScript
Integrations
Azure Machine Learning
Azure Machine Learning
MongoDB
MongoDB
Hadoop
Hadoop
Java
Java
Azure Functions
Azure Functions
Azure Container Service
Azure Container Service
Azure Storage
Azure Storage
Azure Websites
Azure Websites
Apache Spark
Apache Spark
Python
Python
No integrations available

What are some alternatives to Azure Cosmos DB, MarkLogic?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Amazon DynamoDB

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.

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