CrateDB Features

Functions when integrated with multiple forms of external applications.

Allows admisistrators to manage and organize storage, networks, and datacenters.

Monitors performance and statistics related to memory, caches and connections.

Alerts users when unauthorized parties or malware is detected allowing administrators to remedy the issue.

Secures data at rest and in transit from unauthorized access.

Allows administrators to organize components of the database to maintain instance efficiency.

Allows the creating and relinquishing of database access credentials.

Documents access and alterations of the database for analytics and reporting.

Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality.

The abillity to restore files to its original loacation or alternative sources on-demand.

Stores historical records of information for reverting or reference.

Helps users navigate databases by labeling and organizing datasets.

Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.

Restores a database to a correct(consistent) state in the event of a failure.

Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc.

Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.

Restores a database to a correct (consistent) state in the event of a failure.

Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc.

Data masking provides an additional layer of access control that can be applied to tables and views.

Verifies identity of database users.

Allows users to gain statistically valid insights from their data while protecting the privacy of individuals.

Provides predefined system roles, privileges, and user-defined roles to users.

Allows integration with external security mechanisms like Kerberos, LDAP authentication etc.

Provides an audit log to track access and operations performed on databases for regulatory compliance.

Provides encryption capability for all the data at rest using encryption keys.

Provides predefined system roles, privileges, and user-defined roles to users.

Allows integration with external security mechanisms like Kerberos, LDAP authentication etc.

Provides an audit log to track access and operations performed on databases for regulatory compliance.

Provides encryption capability for all the data at rest using encryption keys.

Helps in improving the availability of data.

Uses machine learning algorithms to gain actionable insights.

Stores and queries data as JSON-like documents.

Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.

Allows users to index at ingest and query endlessly across data.

Notifies specific events like document inserts, updates, replaces, deletes etc and responds in real-time.

Helps interpret SQL queries and determine the fastest method of execution

Stores frequently-used data in system memory quickly.

Provides support to handle structured, semi-structured, and unstructured data with equal effect.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Allows users to connect business intelligence tools to the database.

Provides support to store, index and query data in more than one format.

Available on multiple operating systems like Linux, Windows, MacOS etc.

Stores data tables as columns.

Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.

Allows semantic search service by organizing data.

Allows indexing of data for search and retrieval.

The feature aids in filtering queries by metadata thus achieving accurate search.

This feature integrates vectors and metadata indexes into a single index.

Aids in faster processing of query to obtain results.

Enables faster queries and search engine-like workloads.

Enables the user to track the time taken for data to be generated and available for processing

Aids in monitoring and reporting data pipeline performance.

Manages in building pipelines between two protocols.

Allows continuous data ingestion directly from the data source.

Aids the database in scaling horizontally and vertically in petabytes.

Helps store the data in fixed size segments called vectors for better management.

Enables ingesting data efficiently and securely.

Allows concurrent access to data without the use of any table locks.