No results found

Your search did not match any results.

We suggest you try the following to help find what you’re looking for:

  • Check the spelling of your keyword search.
  • Use synonyms for the keyword you typed, for example, try “application” instead of “software.”
  • Try one of the popular searches shown below.
  • Start a new search.
Trending Questions
 

Why Customers choose Oracle Autonomous JSON Database over MongoDB Atlas

Oracle Autonomous JSON Database offers features not found in MongoDB Atlas

Oracle Autonomous JSON Database is a cloud document database service that makes it simple to develop JSON-centric applications. It features simple document APIs, serverless scaling, high performance ACID transactions, comprehensive security, and low pay-per-use pricing. Autonomous JSON Database automates provisioning, configuring, tuning, scaling, patching, encrypting, and repairing of databases, eliminating database management and delivering 99.95% availability.

Customers are choosing Oracle over MongoDB Atlas for several reasons:


1. Autonomous JSON Database allows developers to build applications faster with NoSQL style document APIs, have full SQL and PL/SQL access, and use pre-configured low-code environments

Autonomous JSON Database allows developers to rapidly build JSON-centric applications using their preferred programming language with native SODA language drivers and REST APIs. Developers can execute SODA commands from the Oracle SQL Developer Web interface or the SQLcl command line utility, giving them full SQL and PL/SQL access to JSON data using the whole relational database ecosystem of tools and applications. Additionally, application developers and Line of Business (LOB) developers can use the pre-configured Oracle Application Express (APEX) low-code application development environment to create applications faster and with less code than traditional software development approaches.

Capability and evidence
Oracle Autonomous JSON Database
MongoDB Atlas
Is the service optimized for database usage?
Oracle's binary JSON (OSON) format is optimized for efficient database operations. Its offset information allows 'jumps' to selected values, piecewise updates limit transaction log size, and a compression scheme that reduces the JSON document’s physical size.

MongoDB Atlas' BSON format requires more IO when reading and writing data. In addition, the BSON format is limited to 16 MB compared to Oracle’s support of 32 MB documents, requiring greater segmentation of data into multiple documents.
yes
no
Does the service provide full SQL support?
Oracle Autonomous JSON Database combines the best of JSON document stores with SQL, resulting in a no-compromise document database. Developers use simple, modern document database APIs when they want and the full power of SQL when they need it. SQL referential constraints, joins, views, and support for executing long-running transactions allow users to generate cross-collection queries, achieve parallel scalability, and perform advanced analytics that are not possible in MongoDB Atlas.

MongoDB Atlas lacks basic SQL database functionality which must be re-implemented with hundreds of lines of code, tested, and maintained, increasing development and maintenance costs. Implementing SQL-like capabilities within MongoDB Atlas can also create security vulnerabilities if logic accesses data outside the protected database.
yes
no
Does the service provide comprehensive relational capabilities?
Autonomous JSON Database offers full multi-model capabilities, including Full Text search over the JSON data based on Oracle Text. Oracle Text is architected to be JSON document-aware so that searches can be restricted to specific fragments of JSON documents and it can be used for value and range searches. When developers need support for non-JSON data types such as XML, Spatial, and Graph, they can upgrade to the full power of Oracle Autonomous Transaction Processing with a simple push of a button. This upgrade does not require any application updates, code changes, or data migration.

When MongoDB Atlas developers need to incorporate additional data types, access methods, and analytics not present in JSON, they must integrate their application with other databases and move the data to those databases, fragmenting the data and making it more difficult to track for compliance purposes. Application development is slower because developers must integrate multiple single-purpose databases with potentially different APIs into their applications. Security fragmentation caused by using multiple databases may also increase risks.
yes
no
Are optimized machine learning capabilities built into the database?
Autonomous JSON Database eliminates the need to move data to separate machine learning engines by running machine learning algorithms inside the database. Users are not required to learn specialized tools and achieve inference-based insights faster because copy-and-reformat wait times are eliminated. Enterprise data security is also enhanced because strong database encryption and security are always enforced.

MongoDB Atlas lacks built-in machine learning algorithms. Instead, users must export data and use separate, stand-alone machine learning services to build models and run inferences against database data. Using multiple services increases management complexity, forces users to learn specialized tools, and slows the creation and application of machine learning models since data needs to be copied and reformatted. Using multiple services also leads to data fragmentation, creating potential security gaps.
yes
no
Does the service support low-code application development?
Autonomous JSON Database is preconfigured with Application Express (APEX), a highly productive, no-code/low-code environment. As described in a Pique Solutions study (PDF), APEX enables developers and power users to build data-driven JSON-centric applications up to 38X faster and with 95% less code than traditional application development approaches.

MongoDB Atlas does not have an equivalent of Oracle APEX. To implement applications with low-code tools, developers and business users will need to use third-party tools, learn to uses them, and incur additional costs.
yes
no
DSC logo
Oracle’s latest Autonomous JSON Database blows away the MongoDB Atlas service. Autonomous JSON processing 2-3 times faster than MongoDB Atlas means much less time to complete a job. Less time processing equals less money spent. In the cloud, time truly is money.

Marc Staimer Founder and President of DS Consulting and Wikibon Analyst


2. Autonomous JSON Database simplifies operations with machine learning-driven automation for full lifecycle management

Oracle Autonomous JSON Database minimizes database administration overhead by automating the provisioning, configuring, securing, tuning, and scaling of JSON databases. Eliminating complex manual DBA tasks significantly reduces ongoing management and administrative costs, while developers are free to focus on building innovative, content-rich applications. Oracle Autonomous JSON Database increases application tier availability, enabling applications to be continuously available across infrastructure failures and during planned maintenance, unplanned outages, and load imbalances.

Capability and evidence
Oracle Autonomous JSON Database
MongoDB Atlas
Does the service automatically select the type of nodes it’s using?
Autonomous JSON Database uses the same type of scalable, high-performance Oracle Exadata compute and storage resources regardless of workload. Support for up to 256 vCPUs provides more than 2.6X peak performance compared to MongoDB Atlas.

MongoDB Atlas runs on infrastructure from three different IaaS providers, has three types of nodes, and offers 45 different options to choose from. While choice may sound attractive, users must sort through these options, decide on the best and test their applications against each one they select. In addition, the maximum service size is 96 vCPUs, less than 40% of what’s available with Autonomous JSON Database.
yes
no
Does the service support unlimited storage for JSON collections?
Autonomous JSON Database does not have a storage limit for JSON collections. Organizations can create enterprise-wide document databases without worrying about running into capacity constraints or having to increase configuration complexity. In addition, storage is provisioned separately from compute, so you can minimize costs for very large Autonomous JSON databases by only using a few vCPUs.

MongoDB Atlas storage is dependent on the type, size, and IaaS provider that the cluster is running on. Customers must pay for the additional compute that comes with the storage, even if they don’t typically need it. The maximum MongoDB Atlas document store is 4 TB—which comes with 96 vCPUs. However, clusters with 8 vCPUs may be limited to document stores as small as 128 GB. Expanding beyond MongoDB Atlas’ 4 TB limit requires customers to use sharding across multiple databases, increasing complexity and costs.
yes
no
Does the service auto-tune itself to deliver optimal performance based on dynamic workloads?
Autonomous JSON Database automatically configures and tunes itself as data and schema change over time. Memory configurations, data formats, indexes, and access structures are automatically optimized to improve performance. No DBA involvement is needed.

MongoDB Atlas does not provide any auto-tuning capabilities. Developers or DBAs must manually tune multiple aspects of the database, from creating indexes to searching for storage wait states, locking performance, and cluster overload. Manually tuning the MongoDB database takes time and effort and may result in sub-optimal performance as workloads change.
yes
no
Does the service automatically repair itself?
Autonomous JSON Database continuously monitors hardware and software to identify faults, predict failures, and resolve issues before they impact database operations. If faults occur, high-performance database operations are maintained with complete application transparency by immediately redirecting IO operations to healthy devices with redundant data copies.

MongoDB Atlas will automatically reconfigure itself when faults occur, but it does not offer immediate failover or application transparency. MongoDB Atlas typically pauses for 12 seconds during cluster failovers and elections, forcing customers to add retry logic to their applications to handle the delays.
yes
no
Does the service offer automatic failover to standby systems with zero administration and zero data loss?
Autonomous JSON Database can automatically fail over to a standby system with no data loss using Autonomous Data Guard. All capabilities of Autonomous JSON Database are transferred to the standby system, which is automatically kept up to date.

MongoDB Atlas uses a replica set, a primary and secondary, as the mechanism for redundancy and data availability. However, Multi-document transactions that contain read operations must use the primary database, and all operations in a given transaction must route to the same member. This can result in users seeing inconsistent read results before the writes are propagated to the secondary copy.
yes
no
Constellation logo
With Oracle Autonomous JSON Database service, the administrative and operational aspect of JSON-based next gen Apps is taken care of, and the result is both a better developer experience and higher developer velocity.

Holger Mueller VP and Principal Analyst, Constellation


3. Autonomous JSON Database achieves higher performance on multi-document ACID transactions with optimized formats and high-performance infrastructure

Oracle Autonomous JSON Database runs up to 3.2X faster than MongoDB Atlas when using the same amount of compute infrastructure, as demonstrated in benchmark tests using the industry-standard Cloud Serving Benchmark (YCSB). You can click here to replicate the benchmark yourself. Autonomous JSON Database automatically scales to deliver high performance despite changes in data volume, query complexity, and number of concurrent users. Furthermore, Autonomous JSON Database is built upon Oracle’s long history of supporting ACID transactions, increasing data validity for multi-document transactions. As a result, the time and cost to complete transactions on single or multiple documents can be much lower on Oracle vs MongoDB.

Capability and evidence
Oracle Autonomous JSON Database
MongoDB Atlas
Does the service deliver high performance without sacrificing ACID transaction consistency?
Autonomous JSON Database is built on the proven Oracle Database platform, using Oracle Exadata infrastructure to provide low-latency Create, Read, Update, and Delete (CRUD) operations; and maintains full ACID transaction consistency for enterprise applications. Autonomous JSON Database eliminates data corruption and data loss when performing a sequence of write operations on multiple documents as a single transaction.

MongoDB Atlas is not a transactional database. Its support for multi-document ACID transactions was only introduced in May 2018. MongoDB Atlas’ ACID capabilities come with many limitations that come up short on supporting consistency. For instance, it is recommended that MongoDB Atlas users not update to more than 1,000 documents in a transaction in order to limit the possibility that the transaction will be aborted due to timeouts. Developers are forced to work around these limitations by writing their own bulk updates with error checks, commits, and rollback logic. Third-party reviewers also confirmed the limitations of MongoDB Atlas’ ACID transactions.
yes
no
Does the service deliver superior performance?
Autonomous JSON Database’s native JSON binary format, OSON, is highly optimized for fast reads, avoiding linear scans and partial updates while reducing redo/undo log sizes. As a result, Autonomous JSON Database significantly outperforms MongoDB Atlas. As the performance benchmark demonstrates, Autonomous JSON Database is up to 3.2X faster than MongoDB Atlas for workloads represented by the YCSB benchmark.

MongoDB Atlas' binary format, BSON, requires linear scans and full document updates, causing it to run slower than Autonomous JSON Database. In addition, documents stored in BSON typically take up more storage than documents stored in Oracle’s OSON format.
yes
no
Does the service automatically scale itself on a granular level to optimize query performance and concurrent user throughput while limiting costs?
Autonomous JSON Database automatically scales compute resources to optimize query performance and concurrent user throughput requirements. Compute resources are automatically and instantly scaled down when they are no longer needed. Compute and storage scaling take place independently, so increasing storage capacity does not force higher compute costs. Organizations only pay for the minimum level of compute resources they consume.

MongoDB Atlas automatically scales clusters to the next sizing tier, but this scaling is neither granular nor instantaneous—and differs based on which IaaS provider a customer selects. For example, general purpose clusters range in size from 1 vCPU to 96 vCPUs in size, with all sizes except 48 vCPUs and 96 vCPUs being based on power-of-two scaling. As a result, auto-scaling an M60 cluster with 16 vCPUs requires doubling the size to 32 vCPUs and doubling costs even if only a small increase is needed. Automatically scaling down a cluster can only take place once every 24 hours, only happens one tier size at a time, and only takes place once average CPU and memory utilization over the past 24 hours is below 50%. Increasing storage capacity on MongoDB Atlas typically also requires paying for additional compute resources. MongoDB Atlas customers may pay up to 4 times more than needed during times of low usage.
yes
no
Wikibon logo
Oracle Autonomous JSON Database is up to 3.2 times faster than MongoDB Atlas and up to 4.1 times faster than Amazon DocumentDB for workloads represented by the YCSB benchmark.

David Floyer Chief Technology Officer, Wikibon


4. Autonomous JSON Database is secure by design with always-on encryption and Oracle Data Vault that provides strong data protection from external and internal threats with comprehensive data security

Autonomous JSON Database is secure by design, providing multi-layered security in the cloud and keeping data safe from both outsider and insider threats. Automatic encryption continuously protects data-at-rest and in motion, including during backups and across network connections. Automated application of security patches without downtime reduces potential windows of vulnerability, while detailed auditing and separation of management roles helps reduce internal threats. Organizations also use Oracle Data Safe to conduct ongoing security assessments, user and privilege analysis, sensitive data discovery, sensitive data protection, and activity auditing.

Capability and evidence
Oracle Autonomous JSON Database
MongoDB Atlas
Does the service include a comprehensive way to monitor and manage security?
Autonomous JSON Database comes with Oracle Data Safe at no additional charge. Oracle Data Safe helps customers understand the sensitivity of their data, evaluate risks to data, implement and monitor security controls, assess user security, monitor user activity, mask sensitive data, and address data security compliance requirements.

MongoDB Atlas has basic security features such as authentication, authorization, encryption, network isolation, and database auditing, but lacks the equivalent Oracle Data Safe functionality. Organizations must implement Data Safe-like features using third-party tools to secure their data, increasing risk and operational and administrative costs.
yes
no
Does the service provide security controls to prevent privileged users from accessing sensitive data?
Autonomous JSON Database comes with Oracle Database Vault, which provides powerful security controls to protect application data against unauthorized access to address privacy and regulatory requirements. Controls can be deployed to block privileged account access to application data and control sensitive operations inside the database.

MongoDB Atlas does not offer this capability, and currently cannot provide preventive controls to block privileged users and DBAs from accessing sensitive data in the database.
yes
no
Does the service support extensive government and industry certifications?
Autonomous Database supports a broad suite of compliance attestations and certifications, including HIPPA, ISO/IEC 27001:2013, ISO 27017:2015, ISO 27018: 2014, SOC 1, SOC 2, FISC, NISC, and NCSC guidelines. In addition, Oracle Cloud Infrastructure has been successfully evaluated for a number of operational standards.

In contrast, MongoDB Atlas provides a very limited set of certifications, including HIPPA, SOC2, and ISO/IEC 27001:2013.
yes
no
Can the service be deployed in customer data centers to meet data sovereignty requirements?
Oracle Autonomous Transaction Processing supports a superset of Autonomous JSON Database features, and is available in customers’ data centers on Oracle Exadata Cloud@Customer allowing customers to gain cloud economics and meet data sovereignty and security requirements. Running Autonomous Transaction Processing on Exadata Cloud@Customer also provides high-performance / low-latency connectivity to existing IT infrastructure while achieving the cost and operational benefits of using a cloud document database.

MongoDB Atlas does not provide equivalent functionality, and it is not available on AWS Outposts, Azure Stack, or GCP Anthos. Customers who wish to use MongoDB on-premises must license, install, manage, and secure MongoDB Enterprise Server on their own infrastructure in a do-it-yourself type of environment.
yes
no
IDC logo

The Security Benefits of a Fully Managed Database Service: Oracle Autonomous Database


5. Autonomous JSON Databases reduces total cost of ownership with built-in features and automatic scaling

Autonomous JSON Database provides significant savings on total cost of ownership compared to MongoDB Atlas due to lower cost per-second billing, auto-scaling, autonomous operations, and higher performance that results in lower resource utilization. Organizations are only charged for what they actually use.

Capability and evidence
Oracle Autonomous JSON Database
MongoDB Atlas
Does the service provide lower subscription pricing?
Autonomous JSON Database provides 30% lower subscription pricing than a comparable MongoDB Atlas service for the same memory, CPU, and storage, reducing a customer’s total cost of ownership.
yes
no
Does the service offer true pay-per-use with per-second billing?
Autonomous JSON Database offers per-second billing with real-time up and down scaling of resource consumption to create a true pay-per-use pricing model.

MongoDB Atlas does not offer per-second billing, and auto-scaling to smaller clusters occurs only once per day, leading to substantially higher costs.
yes
no
Does the service provide cost savings via autonomous operations?
Autonomous JSON Database automates many tasks—provisioning, configuring, tuning, scaling, patching, encrypting, and repairing of databases—that significantly reduce the amount of effort to deploy and manage the database.

MongoDB Atlas requires much greater hands-on operations, resulting in higher administration costs.
yes
no
Does the service provide cost savings through higher performance?
Autonomous JSON Database delivers up to 3.2X higher performance on similar infrastructure when compared to MongoDB Atlas. When combined with 30% lower costs for comparable infrastructure, Autonomous JSON Database provides potential savings of up to 85% compared to MongoDB Atlas.
yes
no
Winter Corporation logo
Oracle has priced Autonomous JSON Database to be competitive with MongoDB Atlas and AWS DocumentDB in a low-end (8 OCPU) configuration. As customers scale up from this configuration, however, they have more granular scaling options with Oracle, which combined with faster performance can result in cost savings in comparison to the fixed shape scaling and slower performance associated with other options.

Richard Winter Winter Corporation

Start a free Autonomous JSON Database trial.