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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
PawSQL embodies the leading practices of query optimization within the database sector, offering sophisticated SQL rewrite enhancements and advanced index suggestions aimed at addressing sluggish queries. Leveraging the expertise of its professional optimization engine, which boasts a user base of over 10,000 database professionals globally, PawSQL delivers an extensive array of SQL optimization advice along with smart index recommendations. Additionally, it features a well-rounded audit rule framework designed for various database systems, including MySQL, PostgreSQL, openGauss, and Oracle, ensuring that enterprises enjoy a uniform auditing experience across their diverse database landscapes. The rule-oriented SQL evaluation focuses on identifying potential correctness flaws and opportunities for performance enhancement. By providing rich rewrite optimization, it suggests semantically equivalent yet more efficient SQL queries, while the cost-based validation confirms that the proposed solutions from SQL rewrites and index recommendations yield superior performance outcomes. Furthermore, PawSQL’s intelligent index recommendation feature enables users to optimize their query performance effectively.
API Access
Has API
API Access
Has API
Integrations
MySQL
PostgreSQL
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
DataGrip
MariaDB
OpenMetadata
Integrations
MySQL
PostgreSQL
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
DataGrip
MariaDB
OpenMetadata
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
PawSQL
Founded
2024
Country
China
Website
www.pawsql.com
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Product Features
Database Monitoring
Anomaly Detection
Autodiscovery
Capacity Planning
Dashboard
Dependency Tracking
Historical Trend Analysis
Multitenancy
Notifications / Alerts
Performance Monitoring
Permissions / Access Controls
Predictive Analytics
Prioritization
Query Analysis
Resource Optimization
Troubleshooting