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ease
features
design
support

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Description

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Description

With your data now actively flowing, it's essential to extract meaningful insights from it. Stream processing allows for immediate analysis of your data streams, though establishing the necessary infrastructure can be a daunting task. To address this challenge, Confluent has introduced ksqlDB, a database specifically designed for applications that require stream processing. By continuously processing data streams generated across your organization, you can turn your data into actionable insights right away. ksqlDB features an easy-to-use syntax that facilitates quick access to and enhancement of data within Kafka, empowering development teams to create real-time customer experiences and meet operational demands driven by data. This platform provides a comprehensive solution for gathering data streams, enriching them, and executing queries on newly derived streams and tables. As a result, you will have fewer infrastructure components to deploy, manage, scale, and secure. By minimizing the complexity in your data architecture, you can concentrate more on fostering innovation and less on technical maintenance. Ultimately, ksqlDB transforms the way businesses leverage their data for growth and efficiency.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hue
SQL
Baidu Sugar
Equalum
Google Cloud Bigtable
IBM Intelligent Operations Center for Emergency Mgmt
IBM SPSS Modeler
Intel Tiber AI Studio
MLlib
Mage Platform
Medical LLM
Onehouse
Oxla
PySpark
Querona
RunCode
StreamFlux
Tabular
Tonic Ephemeral

Integrations

Hue
SQL
Baidu Sugar
Equalum
Google Cloud Bigtable
IBM Intelligent Operations Center for Emergency Mgmt
IBM SPSS Modeler
Intel Tiber AI Studio
MLlib
Mage Platform
Medical LLM
Onehouse
Oxla
PySpark
Querona
RunCode
StreamFlux
Tabular
Tonic Ephemeral

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

spark.apache.org

Vendor Details

Company Name

Confluent

Founded

2014

Country

United States

Website

www.confluent.io/product/ksqldb/

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 Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Product Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Alternatives

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Alternatives

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The Apache Software Foundation