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Description
Iceberg is an advanced format designed for managing extensive analytical tables efficiently. It combines the dependability and ease of SQL tables with the capabilities required for big data, enabling multiple engines such as Spark, Trino, Flink, Presto, Hive, and Impala to access and manipulate the same tables concurrently without issues. The format allows for versatile SQL operations to incorporate new data, modify existing records, and execute precise deletions. Additionally, Iceberg can optimize read performance by eagerly rewriting data files or utilize delete deltas to facilitate quicker updates. It also streamlines the complex and often error-prone process of generating partition values for table rows while automatically bypassing unnecessary partitions and files. Fast queries do not require extra filtering, and the structure of the table can be adjusted dynamically as data and query patterns evolve, ensuring efficiency and adaptability in data management. This adaptability makes Iceberg an essential tool in modern data workflows.
Description
The contemporary data workspace transforms the accessibility of your data assets, making everything from data tables to BI reports easily discoverable. With our robust search algorithms and user-friendly browsing experience, locating the right asset becomes effortless. Atlan simplifies the identification of poor-quality data through the automatic generation of data quality profiles. This includes features like variable type detection, frequency distribution analysis, missing value identification, and outlier detection, ensuring you have comprehensive support. By alleviating the challenges associated with governing and managing your data ecosystem, Atlan streamlines the entire process. Additionally, Atlan’s intelligent bots analyze SQL query history to automatically construct data lineage and identify PII data, enabling you to establish dynamic access policies and implement top-notch governance. Even those without technical expertise can easily perform queries across various data lakes, warehouses, and databases using our intuitive query builder that resembles Excel. Furthermore, seamless integrations with platforms such as Tableau and Jupyter enhance collaborative efforts around data, fostering a more connected analytical environment. Thus, Atlan not only simplifies data management but also empowers users to leverage data effectively in their decision-making processes.
API Access
Has API
API Access
Has API
Integrations
Amazon Data Firehose
Anomalo
Apache Flink
Apache Hive
Apache Spark
Daft
Dell AI-Ready Data Platform
Dremio
Google Data Studio
Onehouse
Integrations
Amazon Data Firehose
Anomalo
Apache Flink
Apache Hive
Apache Spark
Daft
Dell AI-Ready Data Platform
Dremio
Google Data Studio
Onehouse
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
Apache Software Foundation
Founded
1999
Country
United States
Website
iceberg.apache.org
Vendor Details
Company Name
Atlan
Founded
2018
Country
India
Website
atlan.com
Product Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
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 Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Fabric
Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
PIM
Content Syndication
Data Modeling
Data Quality Control
Digital Asset Management
Documentation Management
Master Record Management
Version Control