Rockset Features
What are the features of Rockset?
Query latency
- Lower query latency
- Continuous queries
Data latency
- Lower data latency
Connectors
- Faster ingestion
- Built-in connectors
Scale
- Linearly scalable database
- Storage management
Architecture
- Data security
- Lockless architecture
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Rockset Categories on G2
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Configuration
Application Performance | Functions when integrated with multiple forms of external applications. | Not enough data | |
Database Monitoring | Monitors performance and statistics related to memory, caches and connections. | Not enough data | |
Network Security | Secures data at rest and in transit from unauthorized access. | Not enough data |
Database Administration
Provisioning | Allows administrators to organize components of the database to maintain instance efficiency. | Not enough data | |
Governance | Allows the creating and relinquishing of database access credentials. | Not enough data | |
Auditing | Documents access and alterations of the database for analytics and reporting. | Not enough data |
Availability
Scalability | Expands functionality while maintaining balanced loads. Serves growing demand without reducing functionality. | Not enough data | |
Backup | The abillity to restore files to its original loacation or alternative sources on-demand. | Not enough data | |
Archiving | Stores historical records of information for reverting or reference. | Not enough data | |
Indexing | Helps users navigate databases by labeling and organizing datasets. | Not enough data |
Database
Real-Time Data Collection | Collects, stores, and organizes massive, unstructured data in real time | Not enough data | |
Data Distribution | Facilitates the disseminating of collected big data throughout parallel computing clusters | Not enough data | |
Data Lake | Creates a repository to collect and store raw data from sensors, devices, machines, files, etc. | 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 |
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 Transformation
Real-Time Analytics | Facilitates analysis of high-volume, real-time data. | Not enough data | |
Data Querying | Allows user to query data through query languages like SQL. | Not enough data |
Connectivity
Multi-Source Analysis | Integrates data from multiple external databases. | Not enough data | |
Data Lake | Facilitates the dissemination of collected big data throughout parallel computing clusters. | Not enough data |
Operations
Data Visualization | Processes data and represents interpretations in a variety of graphic formats. | Not enough data | |
Data Workflow | Strings together specific functions and datasets to automate analytics iterations. | Not enough data | |
Embedded Analytics | Allows big data tool to run and record data within external applications. | Not enough data | |
Notebooks | Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations | Not enough data |
Security
Data Masking | Data masking provides an additional layer of access control that can be applied to tables and views. | Not enough data | |
Authentication And Single Sign-On | Verifies identity of database users. | Not enough data | |
Data Anonymization | Allows users to gain statistically valid insights from their data while protecting the privacy of individuals. | Not enough data |
Data Management
Data Replication | Helps in improving the availability of data. | Not enough data | |
Advanced Data Analytics | Uses machine learning algorithms to gain actionable insights. | Not enough data |
Data Indexing
Semantic Search | Allows semantic search service by organizing data. | Not enough data | |
Indexing Data | Allows indexing of data for search and retrieval. | Not enough data |
Filters
Accurate Search | The feature aids in filtering queries by metadata thus achieving accurate search. | Not enough data | |
Single Stage Filtering - Vector Database | This feature integrates vectors and metadata indexes into a single index. | Not enough data |
Query latency
Lower query latency | Aids in faster processing of query to obtain results. This feature was mentioned in 19 Rockset reviews. | 89% (Based on 19 reviews) | |
Continuous queries | Based on 18 Rockset reviews. Enables faster queries and search engine-like workloads. | 92% (Based on 18 reviews) |
Data latency
Lower data latency | Enables the user to track the time taken for data to be generated and available for processing 18 reviewers of Rockset have provided feedback on this feature. | 90% (Based on 18 reviews) |
Connectors
Faster ingestion | Manages in building pipelines between two protocols. This feature was mentioned in 19 Rockset reviews. | 89% (Based on 19 reviews) | |
Built-in connectors | Allows continuous data ingestion directly from the data source. 18 reviewers of Rockset have provided feedback on this feature. | 83% (Based on 18 reviews) |
Scale
Linearly scalable database | Based on 19 Rockset reviews. Aids the database in scaling horizontally and vertically in petabytes. | 88% (Based on 19 reviews) | |
Storage management | Helps store the data in fixed size segments called vectors for better management. 19 reviewers of Rockset have provided feedback on this feature. | 87% (Based on 19 reviews) |
Architecture
Data security | Based on 18 Rockset reviews. Enables ingesting data efficiently and securely. | 91% (Based on 18 reviews) | |
Lockless architecture | As reported in 18 Rockset reviews. Allows concurrent access to data without the use of any table locks. | 90% (Based on 18 reviews) |
