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Description
Apache Avro™ serves as a system for data serialization, offering intricate data structures and a fast, compact binary format along with a container file for persistent data storage and remote procedure calls (RPC). It also allows for straightforward integration with dynamic programming languages, eliminating the need for code generation when reading or writing data files or implementing RPC protocols; this only becomes a recommended optimization for statically typed languages. Central to Avro's functionality is its reliance on schemas, which accompany the data at all times, ensuring that the schema used for writing is always available during reading. This design choice minimizes the overhead per value, resulting in both rapid serialization and reduced file size. Furthermore, it enhances compatibility with dynamic and scripting languages since the data is entirely self-describing along with its schema. When data is saved in a file, its corresponding schema remains embedded within, allowing for subsequent processing by any compatible program. In instances where the reading program anticipates a different schema, this discrepancy can be resolved with relative ease, showcasing Avro's flexibility and efficiency in data management. Overall, Avro's architecture significantly streamlines the handling of data across a variety of programming environments.
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 DataFusion
Apache Hive
Arroyo
Beats
Data Sentinel
Eco
Hackolade
Hive
Micromerce
Integrations
AWS IoT SiteWise
Apache DataFusion
Apache Hive
Arroyo
Beats
Data Sentinel
Eco
Hackolade
Hive
Micromerce
Pricing Details
No price information available.
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
avro.apache.org
Vendor Details
Company Name
Upsolver
Founded
2014
Country
Israel
Website
www.upsolver.com
Product Features
DevOps
Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports
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