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Storage
Availability
Stability
Scalability
Security
Data Manipulation
Query Language
Real-Time Data Collection
10 reviewers of Druid have provided feedback on this feature.
Collects, stores, and organizes massive, unstructured data in real time
Data Distribution
This feature was mentioned in 10 Druid reviews.
Facilitates the disseminating of collected big data throughout parallel computing clusters
Data Lake
Creates a repository to collect and store raw data from sensors, devices, machines, files, etc.
Hadoop Integration
Aligns processing and distribution workflows on top of Apache Hadoop
Spark Integration
Machine Scaling
Facilitates solution to run on and scale to a large number of machines and systems
Data Preparation
Curates collected data for big data analytics solutions to analyze, manipulate, and model
Cloud Processing
Moves big data collection and processing to the cloud
Workload Processing
Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems
Data Integration
Consolidates, Cleanses and Normalizes data from multiple disparate sources.
Data Compression
Helps save storage capacity and improves query performance.
Data Quality
Eliminates data inconsistency and duplications ensuring data integrity.
Built-In Data Analytics
SQL based analytics functions like Time series, pattern matching, geospatial analytics etc.
In-Database Machine Learning
Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc.
Data Lake Analytics
Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS
AI/ ML Integration
Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities.
BI Tool Integration
Integrates with BI Tools to transform data into Actionable Insights.
Data lake Integration
Provides speed in data processing and capturing unstructured, semi-structured and streaming data.
On-Premise
Provides On-Premise deployment options.
Cloud
Provides Cloud deployment options (private or public cloud, hybrid cloud).
Manages huge volumes of data, upscale or downscale as per demand.
Disaster Recovery
Provides data recovery functionality to protect and restore data in a database.
Data Concurrency
Allows multi-version concurrency control.
Workload Management
Handles workloads, from single machines to data warehouses or web services with many concurrent users.
Advanced Indexing
Allows users to quickly retrieve data through various types of indexing like B-tree, hash table etc.
Query Optimizer
Helps interpret SQL queries and determine the fastest method of execution.
Text Search
Provides support for international character sets and full text search.
Data Types
Supports multiple data types like primitive, structured, document etc.
Languages
Supports multiple procedural programming languages like PL/PGSQL, Perl, Python etc.
Operating Systems
Available on multiple operating systems like Linux, Windows, MacOS etc.
Database Locking
Prevents other users and applications from accessing data while it is being updated to avoid data loss or update.
Access Control
Allows permissions to be granted or revoked in the database, schema or table levels.
Encryption
Built-in native encryption with enterprise key management.
Authentication
Provides multi-factor authentication with certificates.
Data Governance
Policies, procedures and standards to manage and access data.
Data Security
Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion
Role-Based Authorization
Provides predefined system roles, privileges, and user-defined roles to users.
Allows integration with external security mechanisms like Kerberos, LDAP authentication etc.
Audit Logs
As reported in 10 Druid reviews.
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.
Data Schema
Data is organized as a set of tables with columns and rows like a table structure.
Allows users to create, update and retrieve data in a database.
ACID - Complaint
Adheres to ACID (atomicity, consistency, isolation, durability), a set of database transaction properties.
Data Replication
Provides log-based or/and trigger-based replication.
Data Model
Based on 10 Druid reviews.
Stores data tables as columns.
Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc.
Auto Sharding
Implements auto horizontal data partitioning that allows storing data on more than one node to scale out.
Auto Recovery
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.
Integrated Cache
Stores frequently-used data in system memory quickly.
Multi-Model
Provides support to store, index and query data in more than one format.
Based on 11 Druid reviews.
Lower query latency
Aids in faster processing of query to obtain results.
Continuous queries
Enables faster queries and search engine-like workloads.
Lower data latency
Enables the user to track the time taken for data to be generated and available for processing
Data pipeline performance
Aids in monitoring and reporting data pipeline performance.
Faster ingestion
Manages in building pipelines between two protocols.
Built-in connectors
Allows continuous data ingestion directly from the data source.
Linearly scalable database
Aids the database in scaling horizontally and vertically in petabytes.
Storage management
Helps store the data in fixed size segments called vectors for better management.
Data security
Enables ingesting data efficiently and securely.
Lockless architecture
Allows concurrent access to data without the use of any table locks.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
