Druid Features
What are the features of Druid?
Database
- Real-Time Data Collection
- Data Distribution
Security
- Audit Logs
Storage
- Data Model
- Data Types
Availability
- Data Replication
Support
- Multi-Model
- Operating Systems
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Druid Categories on G2
Filter for Features
Database Features
Storage | Not enough data | ||
Availability | Not enough data | ||
Stability | Not enough data | ||
Scalability | Not enough data | ||
Security | Not enough data | ||
Data Manipulation | See feature definition | Not enough data | |
Query Language | Not enough data |
Database
Real-Time Data Collection | Based on 10 Druid reviews. Collects, stores, and organizes massive, unstructured data in real time | 85% (Based on 10 reviews) | |
Data Distribution | Facilitates the disseminating of collected big data throughout parallel computing clusters This feature was mentioned in 10 Druid reviews. | 87% (Based on 10 reviews) | |
Data Lake | Creates a repository to collect and store raw data from sensors, devices, machines, files, etc. | Not enough data |
Integrations
Hadoop Integration | Aligns processing and distribution workflows on top of Apache Hadoop | Not enough data | |
Spark Integration | Aligns processing and distribution workflows on top of Apache Hadoop | Not enough data |
Platform
Machine Scaling | Facilitates solution to run on and scale to a large number of machines and systems | Not enough data | |
Data Preparation | Curates collected data for big data analytics solutions to analyze, manipulate, and model | Not enough data | |
Spark Integration | Aligns processing and distribution workflows on top of Apache Hadoop | Not enough data |
Processing
Cloud Processing | Moves big data collection and processing to the cloud | Not enough data | |
Workload Processing | Processes batch, real-time, and streaming data workloads in singular, multi-tenant, or cloud systems | Not enough data |
Data Management
Data Integration | Consolidates, Cleanses and Normalizes data from multiple disparate sources. | Not enough data | |
Data Compression | Helps save storage capacity and improves query performance. | Not enough data | |
Data Quality | Eliminates data inconsistency and duplications ensuring data integrity. | Not enough data | |
Built-In Data Analytics | SQL based analytics functions like Time series, pattern matching, geospatial analytics etc. | Not enough data | |
In-Database Machine Learning | Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc. | Not enough data | |
Data Lake Analytics | Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS | Not enough data |
Integration
AI/ ML Integration | Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities. | Not enough data | |
BI Tool Integration | Integrates with BI Tools to transform data into Actionable Insights. | Not enough data | |
Data lake Integration | Provides speed in data processing and capturing unstructured, semi-structured and streaming data. | Not enough data |
Deployment
On-Premise | Provides On-Premise deployment options. | Not enough data | |
Cloud | Provides Cloud deployment options (private or public cloud, hybrid cloud). | Not enough data |
Performance
Scalability | Manages huge volumes of data, upscale or downscale as per demand. | Not enough data | |
Disaster Recovery | Provides data recovery functionality to protect and restore data in a database. | Not enough data | |
Data Concurrency | Allows multi-version concurrency control. | Not enough data | |
Workload Management | Handles workloads, from single machines to data warehouses or web services with many concurrent users. | Not enough data | |
Advanced Indexing | Allows users to quickly retrieve data through various types of indexing like B-tree, hash table etc. | Not enough data | |
Query Optimizer | Helps interpret SQL queries and determine the fastest method of execution. | Not enough data |
Support
Text Search | Provides support for international character sets and full text search. | Not enough data | |
Data Types | Supports multiple data types like primitive, structured, document etc. | Not enough data | |
Languages | Supports multiple procedural programming languages like PL/PGSQL, Perl, Python etc. | Not enough data | |
Operating Systems | Available on multiple operating systems like Linux, Windows, MacOS etc. | Not enough data |
Security
Database Locking | Prevents other users and applications from accessing data while it is being updated to avoid data loss or update. | Not enough data | |
Access Control | Allows permissions to be granted or revoked in the database, schema or table levels. | Not enough data | |
Encryption | Built-in native encryption with enterprise key management. | Not enough data | |
Authentication | Provides multi-factor authentication with certificates. | Not enough data | |
Data Governance | Policies, procedures and standards to manage and access data. | Not enough data | |
Data Security | Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion | Not enough data | |
Role-Based Authorization | Provides predefined system roles, privileges, and user-defined roles to users. | Not enough data | |
Authentication | Allows integration with external security mechanisms like Kerberos, LDAP authentication etc. | Not enough data | |
Audit Logs | Provides an audit log to track access and operations performed on databases for regulatory compliance. This feature was mentioned in 10 Druid reviews. | 87% (Based on 10 reviews) | |
Encryption | Provides encryption capability for all the data at rest using encryption keys. | Not enough data |
Management
Data Schema | Data is organized as a set of tables with columns and rows like a table structure. | Not enough data | |
Query Language | Allows users to create, update and retrieve data in a database. | Not enough data | |
ACID - Complaint | Adheres to ACID (atomicity, consistency, isolation, durability), a set of database transaction properties. | Not enough data | |
Data Replication | Provides log-based or/and trigger-based replication. | Not enough data |
Storage
Data Model | As reported in 10 Druid reviews. Stores data tables as columns. | 88% (Based on 10 reviews) | |
Data Types | As reported in 10 Druid reviews. Supports multiple data types like lists, sets, hashes (similar to map), sorted sets etc. | 78% (Based on 10 reviews) |
Availability
Auto Sharding | Implements auto horizontal data partitioning that allows storing data on more than one node to scale out. | Not enough data | |
Auto Recovery | Restores a database to a correct (consistent) state in the event of a failure. | Not enough data | |
Data Replication | Copy data across multiple servers through master-slave, peer-to-peer replication architecture etc. This feature was mentioned in 10 Druid reviews. | 83% (Based on 10 reviews) |
Performance
Integrated Cache | Stores frequently-used data in system memory quickly. | Not enough data |
Support
Multi-Model | Provides support to store, index and query data in more than one format. This feature was mentioned in 10 Druid reviews. | 88% (Based on 10 reviews) | |
Operating Systems | Available on multiple operating systems like Linux, Windows, MacOS etc. This feature was mentioned in 11 Druid reviews. | 92% (Based on 11 reviews) |
Query latency
Lower query latency | Aids in faster processing of query to obtain results. | Not enough data | |
Continuous queries | Enables faster queries and search engine-like workloads. | Not enough data |
Data latency
Lower data latency | Enables the user to track the time taken for data to be generated and available for processing | Not enough data | |
Data pipeline performance | Aids in monitoring and reporting data pipeline performance. | Not enough data |
Connectors
Faster ingestion | Manages in building pipelines between two protocols. | Not enough data | |
Built-in connectors | Allows continuous data ingestion directly from the data source. | Not enough data |
Scale
Linearly scalable database | Aids the database in scaling horizontally and vertically in petabytes. | Not enough data | |
Storage management | Helps store the data in fixed size segments called vectors for better management. | Not enough data |
Architecture
Data security | Enables ingesting data efficiently and securely. | Not enough data | |
Lockless architecture | Allows concurrent access to data without the use of any table locks. | Not enough data |
