Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Pinot is built to efficiently handle OLAP queries on static data with minimal latency. It incorporates various pluggable indexing methods, including Sorted Index, Bitmap Index, and Inverted Index. While it currently lacks support for joins, this limitation can be mitigated by utilizing Trino or PrestoDB for querying purposes. The system offers an SQL-like language that enables selection, aggregation, filtering, grouping, ordering, and distinct queries on datasets. It comprises both offline and real-time tables, with real-time tables being utilized to address segments lacking offline data. Additionally, users can tailor the anomaly detection process and notification mechanisms to accurately identify anomalies. This flexibility ensures that users can maintain data integrity and respond proactively to potential issues.
Description
A cloud database that can scale to handle large streaming data sets. Kinetica harnesses modern vectorized processors to perform orders of magnitude faster for real-time spatial or temporal workloads. In real-time, track and gain intelligence from billions upon billions of moving objects. Vectorization unlocks new levels in performance for analytics on spatial or time series data at large scale. You can query and ingest simultaneously to take action on real-time events. Kinetica's lockless architecture allows for distributed ingestion, which means data is always available to be accessed as soon as it arrives. Vectorized processing allows you to do more with fewer resources. More power means simpler data structures which can be stored more efficiently, which in turn allows you to spend less time engineering your data. Vectorized processing allows for incredibly fast analytics and detailed visualizations of moving objects at large scale.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon S3
Yes
Apache Kafka
Yes
Astro by Astronomer
Yes
Azure Data Lake
Yes
Gravity Data
No
Hadoop
Yes
Hue
Yes
NVIDIA RAPIDS
No
Onehouse
Yes
OpenMetadata
Yes
Integrations
Amazon S3
No
Apache Kafka
No
Astro by Astronomer
No
Azure Data Lake
No
Gravity Data
Yes
Hadoop
No
Hue
No
NVIDIA RAPIDS
Yes
Onehouse
No
OpenMetadata
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Apache Corporation
Founded
1954
Country
United Statess
Website
pinot.apache.org
Vendor Details
Company Name
Kinetica
Founded
2009
Country
United States
Website
www.kinetica.com
Product Features
Product Features
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No
Streaming Analytics
Data Enrichment
Yes
Data Wrangling / Data Prep
Yes
Multiple Data Source Support
Yes
Process Automation
Yes
Real-time Analysis / Reporting
Yes
Visualization Dashboards
Yes