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Description
Apache Doris serves as a cutting-edge data warehouse tailored for real-time analytics, enabling exceptionally rapid analysis of data at scale.
It features both push-based micro-batch and pull-based streaming data ingestion that occurs within a second, alongside a storage engine capable of real-time upserts, appends, and pre-aggregation.
With its columnar storage architecture, MPP design, cost-based query optimization, and vectorized execution engine, it is optimized for handling high-concurrency and high-throughput queries efficiently.
Moreover, it allows for federated querying across various data lakes, including Hive, Iceberg, and Hudi, as well as relational databases such as MySQL and PostgreSQL.
Doris supports complex data types like Array, Map, and JSON, and includes a Variant data type that facilitates automatic inference for JSON structures, along with advanced text search capabilities through NGram bloomfilters and inverted indexes.
Its distributed architecture ensures linear scalability and incorporates workload isolation and tiered storage to enhance resource management.
Additionally, it accommodates both shared-nothing clusters and the separation of storage from compute resources, providing flexibility in deployment and management.
Description
UST IQ for AMI Analytics streamlines the entire data engineering process, managing everything from the ingestion of large-scale, high-frequency metering data to delivering comprehensive insights, allowing AMI business operations to prioritize essential decision-making over IT infrastructure concerns. It efficiently collects both real-time and historical data, including meter readings, events, alarms, GIS information, and external data sources, and transforms this information into query-ready formats using a cloud-native, microservices architecture. This setup supports self-service querying, location-aware and role-specific analytics, and proactive exception management, providing operations teams with crucial insights regarding network anomalies, meter performance, outages, and environmental data such as seismic activity or weather patterns. By doing so, it enhances the ability to optimize field crew deployment, avert expensive failures, and improve restoration efforts. The system processes vast quantities of data, handling hundreds of millions of records each day through low-latency micro-batching, typically in 5-minute intervals, while also offering features like 30-day rolling averages and alert-triggered notifications to further support operational efficiency. This comprehensive approach not only accelerates data processing but also ensures that actionable insights are readily available when needed, ultimately leading to improved operational effectiveness.
API Access
Has API
API Access
Has API
Integrations
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
MySQL
OpenMetadata
PostgreSQL
SelectDB
TapData
Integrations
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
MySQL
OpenMetadata
PostgreSQL
SelectDB
TapData
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
doris.apache.org
Vendor Details
Company Name
UST
Country
United States
Website
www.ust.com/en/what-we-do/digital-transformation/data-analytics/ust-iq/ami
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge