Cloudera and PlanetScale are sometimes compared for numerous use cases in Cloud Database Management Systems (DBMS). We have a detailed features table below. You can also customize your requirements and get expert ratings comparing these two solutions against hundreds of data points across Scalability, Security, Lifecycle, Pricing, Use Case Fit, Attack Protection, Access Controls, Integration, Administration, Traffic Management, Policy Management, Compliance, Authentication and Performance.
Cloudera offers a variety of services including CDP DataFlow, CDP Data Hub, CDP Operational Database, CDP Data Engineering, CDP Data Warehouse, and CDP Machine Learning. These services help with organizing, analyzing, and centralizing data. Cloudera also uses several open-source technologies like Kafka, Hive, Flink, and Spark.
PlanetScale is a MySQL-compatible, serverless database powered by Vitess, which helps with database clustering for horizontal scaling. The PlanetScale console provides features for customizing the database, including specific schemas and sharding configurations.
Customize these feature priorities in Taloflow and get expert ratings for your exact use case.
| Feature | Dimensions | Description | Cloudera | PlanetScale |
|---|---|---|---|---|
| Good Pricing for Bounded Consumption |
|
The pricing structure is suitable for use cases where it's equally important to have some scalability to meet changes in resource demand and some pricing predictability. | NA | OK |
| Good Pricing for Burst Usage Pattern |
|
The pricing structure is suitable for addressing various bursts in demand. | NA | OK |
| Good Pricing for Lots of CPU Consumption |
|
The pricing structure is suitable for use cases with lots of CPU consumption. | OK | Poor |
| Good Pricing for Lots of Data |
|
The pricing structure is suitable for use cases with lots of data. | OK | OK |
| Good Pricing for Lots of Data Indexing |
|
The pricing structure is suitable for use cases with lots of data indexing | NA | OK |
| Good Pricing for Lots of Data Transfer |
|
The pricing structure is suitable for use cases with lots of data transfer. | NA | NA |
| Good Pricing for Lots of Memory Consumption |
|
The pricing structure is suitable for use cases with lots of memory consumption. | OK | OK |
| Transport Layer Security |
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Enables transport layer security between database servers and client applications. | OK | Poor |
| User Authentication |
|
Verify the identity of users attempting to access database instances. | OK | Poor |
| Alerting |
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Give timely wanings so that the problems can get resolved quickly. | OK | Poor |
| Automated Management Utilities |
|
Help administrators by automating DBA operations. | OK | Poor |
| Capacity Planning |
|
Capabilities for planning, monitoring and managing system capacity, including storage and system resource utilization. | OK | Poor |
| Change Management |
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Enable change management across multiple instances of the same database. | OK | Poor |
| Containers and Orchestration |
|
Supports external container and orchestration environments like Kubernetes, Docker, etc. | OK | Poor |
| Database Portability |
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Allows moving of the DBMS instance to another instance. | OK | Poor |
| Monitoring |
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Monitor and alert on potential issues, including performance issues. | OK | Poor |
| Operational Reporting |
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Provides reports on day-to-day activities on the DBMS. | OK | Poor |
| Workload Management |
|
Monitor and manage workloads including concurrency, long-running queries, prioritization of competing workloads, etc. | OK | Poor |
| Alteryx |
|
Support available to integrate with Alteryx for metadata management. | Good | Poor |
| Apache Spark |
|
Capability available to integrate with Apache Spark for analytics. | Good | Poor |
| Azure Data Factory |
|
Support available to integrate with Azure Data Factory for data integration. | Good | Poor |
| Boomi |
|
Support available to integrate with Boomi for data integration. | Good | Poor |
| Collibra |
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Support available to integrate with Collibra for metadata management. | Good | Poor |
| Denodo |
|
Support available to integrate with Denodo for metadata management. | Good | Poor |
| Domo |
|
Support available to integrate with Domo for BI and visualization. | Good | Poor |
| Informatica |
|
Support available to integrate with Informatica for data integration. | Great | Poor |
| Knime |
|
Support available to integrate with Knime for analytics. | Good | Poor |
| Metabase |
|
Support available to integrate with Metabase for BI and visualization. | OK | Poor |
| OneTrust |
|
Support available to integrate with OneTrust for metadata management. | OK | Poor |
| Pentaho |
|
Support available to integrate with Pentaho for BI and visualization. | OK | Poor |
| Power BI |
|
Support available to integrate with Power BI for analytics. | Great | Poor |
| Qlik |
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Support available to integrate with Qlik for metadata management. | Great | Poor |
| SAS BI |
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Support available to integrate with SAS BI for BI and visualization. | OK | Poor |
| SnapLogic |
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Support available to integrate with SnapLogic for data integration. | OK | Poor |
| Splunk |
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Capability available to integrate with Splunk for analytics. | Good | Poor |
| Tableau |
|
Support available to integrate with Tableau for analytics. | Good | Poor |
| Talend |
|
Support available to integrate with Talend for data integration. | Great | Poor |
| Zoho BI and Analytics |
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Support available to integrate with Zoho for BI and visualization. | OK | Poor |
| CCPA |
|
Regulation on data protection and privacy of the data tied to residents of California. | Great | NA |
| Data Masking |
|
Selectively obscure column data from users while still allowing access to the column. | OK | Poor |
| FFIEC |
|
Complies with the encryption requirements for all online transaction processing (OLTP) done by financial institutions. | NA | NA |
| FISMA |
|
Compliance with U.S. government legislation that defines a comprehensive framework that protects government information, operations, and assets against threats. | Great | NA |
| FedRAMP |
|
Ensures that the government security requirements outlined in NIST 800-53 are met and supplemented by the PMO of FedRAMP. | Great | NA |
| GDPR |
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Regulation on data protection and privacy of the data tied to citizens and residents of EU countries. | Great | NA |
| HIPAA |
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Demonstrates security and compliance with standards of the healthcare industry. | Great | Great |
| HITRUST |
|
Demonstrates compliance with HITRUST CSF, an industry-agnostic certifiable framework for regulatory compliance and risk management. This framework, developed by the not-for-profit organization HITRUST, contains a set of prescriptive controls that relate to the organizational processes and technical controls for processing, storing, and transmitting sensitive data. | NA | NA |
| IRAP |
|
Australian government standard for assessing the implementation and effectiveness of an organization’s security controls against the Australian government’s security requirements. | NA | NA |
| MTCS |
|
Multi-tier cloud security standard set up by the government of Singapore. | NA | NA |
| PCI |
|
Standard that ensures security guidelines are met for all entities that store, process, or transmit cardholder data and/or sensitive authentication data. | Great | NA |
| PSD2 |
|
Demonstrates compliance with European regulations related to the Payment Services Directive. | Great | NA |
| RBAC |
|
Authorize and restrict access to specific database functions based on the user's role within the organization. | OK | Poor |
| SOC |
|
Standard promoted by the American Institute of CPAs that ensures the integrity and privacy of customer data. | Great | Great |
| SOX |
|
Standard for public companies that ensures that annual audits take place and are legally-required to show evidence of accurate and secure financial reporting. | NA | NA |
| Streaming Data Support |
|
Supports storing, processing or integrating with streaming data. | OK | Poor |
| Automated Query Governance |
|
Analyzes the query and prevents it from executing unless it meets standards. | OK | Poor |
| Automated Tuning |
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Automatically tune functions without the help of administrators. | OK | Poor |
| Clustering |
|
Increases processing power by connecting multiple database instances. | OK | Poor |
| Cost-Based Query Optimizer |
|
Optimize the query based on query plan cost that determines which query plan to run with. | OK | Poor |
| In-Memory Capability |
|
Allows for the usage of a shared cache for faster user access to the data. | Poor | Poor |
| Indexing Technology |
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Retrieve data from the database without having to read all of the data in storage. | OK | Poor |
| Manual Tuning |
|
Allows database administrators to directly make changes to parameters. | OK | Poor |
| Multiple Application Clustered Node |
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Supports running multiple applications across the cluster. | OK | Poor |
| Node Volume Limitation |
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Set a maximum volume for data storage. | OK | Poor |
| Parallel Query Execution |
|
Increases the execution speed of SQL queries by creating multiple query processes that divide the workload of a SQL statement and execute it in parallel. | OK | OK |
| Parallel Utility Execution |
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Supports running utilities such as backup and recovery, free space reclamation, and index rebuild in parallel. | OK | OK |
| Rule-Based Query Optimizer |
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Optimize the query based on a rule set that determines query execution. | Poor | Poor |
| Storage Control |
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Control where data is stored based on specific locations. | OK | Poor |
| Auto-Scaling |
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Analyzes utilization metrics and then adds and removes nodes automatically based on those metrics. | OK | OK |
| Automated Data Backup and Recovery |
|
Supports automatically backing up data in case of loss and setting up secure systems for data recovery. | OK | OK |
| Automated Failover |
|
Supports automated failover to a disaster recovery site. | OK | OK |
| Data Partitioning |
|
Supports dividing data sets and distributing data over multiple servers. | OK | Poor |
| Database Replication |
|
Creates a copy of the data available in the database in a disaster recovery environment. | OK | OK |
| Disaster Recovery |
|
Supports disaster recovery and provides processing continuity when a region fails or becomes unavailable. | OK | OK |
| Fast Export |
|
Quickly export data from the database. | OK | Poor |
| Fast Loader |
|
Enables fast loading of bulk data (high volumes). | OK | Poor |
| Fault Tolerance |
|
Run operations without interruption when one or more components fail. | OK | OK |
| High Availability |
|
Has a high availability environment for running critical production workloads. | OK | OK |
| Network Load Balancing |
|
Distribute the load between application and database servers. | OK | OK |
| Online Patching and Upgrades |
|
Allows for the patching and upgrade of the DBMS without loss of production in a zero-downtime or near-zero-downtime environment. | OK | Poor |
| Redundancy |
|
Supports data redundancy or geographic redundancy. | OK | OK |
| Regional Scalability |
|
Scalable across multiple regions. | OK | Poor |
| VLDB Support |
|
Supports very large databases for online transaction processing (OLTP) applications. | OK | Poor |
| Activity Monitoring |
|
Monitor user activity and alerts when unusual behavior is detected. | OK | Poor |
| Column-Level Security |
|
Filter data and enable access to specific columns in a database table. | OK | Poor |
| Data Encryption |
|
Secure data with encryption in transit or when stored in the cloud. | OK | Poor |
| Group-Level Security |
|
Group users by requirements and enforce security mechanisms for them. | OK | Poor |
| Identity Management |
|
Natively provides identity management or integrates with identity management tools for authentication and access control. | OK | Poor |
| Key Management |
|
Natively provides key management or integrates with key management tools for creating, managing and controlling cryptographic keys. | OK | Poor |
| Row-Level Security |
|
Filter data and enable access to specific rows in a database table. | Poor | Poor |
| SQL Proxy |
|
Provide secure access to your database instance without configuring SSL or using authorized networks. | OK | Poor |
| AI and ML Library |
|
AI and ML libraries to help with data exploration and preparation. | OK | Poor |
| API Access |
|
Access data via APIs with JDBC and ODBC connectors. | OK | Poor |
| Automated Data Mart |
|
Supports managing an ad hoc data mart or data warehouse setup, control and deletion in support of an internal, private cloud computing model. | OK | Poor |
| Bulk Data Loading |
|
Supports fast loading of huge volumes of data. | OK | OK |
| Cloud Object Store Support |
|
Supports cloud object stores like Amazon S3, Azure Blob Storage, or Blackblaze B2. | OK | Poor |
| Data Management |
|
Provides a REST API for accessing and updating data in the database. | OK | Poor |
| Data Mining |
|
Extend SQL or stored procedures for data mining purposes. | OK | Poor |
| Data Virtualization |
|
Support available in the DBMS for data virtualization tools so that it can act as a hub for data collection. | OK | Poor |
| Document Store |
|
Store documents and query data like JSON, XML etc. | OK | Poor |
| Graph Database |
|
Store multi-relationship data coming from graph databases. | OK | Poor |
| Graph Language Support |
|
Offers graph language support to query your data. | OK | Poor |
| Hybrid Cloud |
|
Deployments can span cloud and on-premises environments. | OK | OK |
| Industry Specific Data Models |
|
Supports industry specfic data models for industries like finance, healthcare, retail, etc. | Poor | Poor |
| Integrated Search |
|
Has integrated search capabilities with Elasticsearch, Splunk, etc. | OK | Poor |
| Key Value Support |
|
Store data in a non-relational style using the key-value method. | OK | Poor |
| Logical Data Warehousing |
|
Support available in the DBMS to treat it as a warehouse for analytics, scale and ease of use. | OK | Poor |
| ML Model Creation |
|
Suppors creating and executing machine learning models. | OK | Poor |
| MultiDimensional Tables |
|
Supports multidimensional tables if the database supports OLAP. | OK | Poor |
| MultiDimensional Views |
|
Supports multidimensional views if the database supports OLAP. | OK | Poor |
| OLAP Database Support |
|
Handle analytical queries as well as generate multidimensional data models. | OK | Poor |
| Query Virtualization |
|
Query data managed in another DBMS or file system. | OK | Poor |
| Real-Time Data Loading |
|
Supports continuous or real-time data upload without degrading performance. | OK | Poor |
| Self-Hosted Cloud |
|
Self-hosted option for provisioning cloud infrastructure, including servers, storage, and connectivity. | OK | Poor |
| Serverless Architecture |
|
Support available in the database for a serverless architecture to help manage the workload. | OK | OK |
| Time Series Support |
|
Store data collected over time intervals. | OK | Poor |
| User Defined Function |
|
Create user-defined functions using SQL or JS code. | OK | Poor |
| dbPaaS |
|
The vendor is responsible for all aspects of administration. | OK | OK |
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