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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Materialize is an innovative reactive database designed to provide updates to views incrementally. It empowers developers to seamlessly work with streaming data through the use of standard SQL. One of the key advantages of Materialize is its ability to connect directly to a variety of external data sources without the need for pre-processing. Users can link to real-time streaming sources such as Kafka, Postgres databases, and change data capture (CDC), as well as access historical data from files or S3. The platform enables users to execute queries, perform joins, and transform various data sources using standard SQL, presenting the outcomes as incrementally-updated Materialized views. As new data is ingested, queries remain active and are continuously refreshed, allowing developers to create data visualizations or real-time applications with ease. Moreover, constructing applications that utilize streaming data becomes a straightforward task, often requiring just a few lines of SQL code, which significantly enhances productivity. With Materialize, developers can focus on building innovative solutions rather than getting bogged down in complex data management tasks.

Description

Spark Streaming extends the capabilities of Apache Spark by integrating its language-based API for stream processing, allowing you to create streaming applications in the same manner as batch applications. This powerful tool is compatible with Java, Scala, and Python. One of its key features is the automatic recovery of lost work and operator state, such as sliding windows, without requiring additional code from the user. By leveraging the Spark framework, Spark Streaming enables the reuse of the same code for batch processes, facilitates the joining of streams with historical data, and supports ad-hoc queries on the stream's state. This makes it possible to develop robust interactive applications rather than merely focusing on analytics. Spark Streaming is an integral component of Apache Spark, benefiting from regular testing and updates with each new release of Spark. Users can deploy Spark Streaming in various environments, including Spark's standalone cluster mode and other compatible cluster resource managers, and it even offers a local mode for development purposes. For production environments, Spark Streaming ensures high availability by utilizing ZooKeeper and HDFS, providing a reliable framework for real-time data processing. This combination of features makes Spark Streaming an essential tool for developers looking to harness the power of real-time analytics efficiently.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Kinesis Yes 
Amazon S3 Yes 
Apache Kafka Yes 
Apache Spark No 
DataClarity Unlimited Analytics Yes 
Debezium Yes 
Gravity Data Yes 
Hue Yes 
Orb Yes 
PostgreSQL Yes 
PubNub Yes 
PubSub+ Platform No 

Integrations

Amazon Kinesis No 
Amazon S3 No 
Apache Kafka No 
Apache Spark Yes 
DataClarity Unlimited Analytics No 
Debezium No 
Gravity Data No 
Hue No 
Orb No 
PostgreSQL No 
PubNub No 
PubSub+ Platform Yes 

Pricing Details

$0.98 per hour
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Materialize

Country

United States

Website

materialize.com

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org/streaming/

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Database

Backup and Recovery No 
Creation / Development No 
Data Migration No 
Data Replication No 
Data Search No 
Data Security No 
Database Conversion No 
Mobile Access No 
Monitoring No 
NOSQL No 
Performance Analysis No 
Queries No 
Relational Interface No 
Virtualization No 

Streaming Analytics

Data Enrichment No 
Data Wrangling / Data Prep No 
Multiple Data Source Support No 
Process Automation No 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

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