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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
Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.
API Access
Has API
API Access
Has API
Integrations
AWS IoT SiteWise
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
Eco
Hive
Micromerce
MySQL
Integrations
AWS IoT SiteWise
Apache Flink
Apache Hive
Apache Hudi
Apache Spark
Baidu Palo
Eco
Hive
Micromerce
MySQL
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
Upsolver
Founded
2014
Country
Israel
Website
www.upsolver.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
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
