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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

IBM Analytics for Apache Spark offers a versatile and cohesive Spark service that enables data scientists to tackle ambitious and complex inquiries while accelerating the achievement of business outcomes. This user-friendly, continually available managed service comes without long-term commitments or risks, allowing for immediate exploration. Enjoy the advantages of Apache Spark without vendor lock-in, supported by IBM's dedication to open-source technologies and extensive enterprise experience. With integrated Notebooks serving as a connector, the process of coding and analytics becomes more efficient, enabling you to focus more on delivering results and fostering innovation. Additionally, this managed Apache Spark service provides straightforward access to powerful machine learning libraries, alleviating the challenges, time investment, and risks traditionally associated with independently managing a Spark cluster. As a result, teams can prioritize their analytical goals and enhance their productivity significantly.

Description

The Stackable data platform was crafted with a focus on flexibility and openness. It offers a carefully selected range of top-notch open source data applications, including Apache Kafka, OpenSearch, Trino, and Apache Spark. Unlike many competitors that either promote their proprietary solutions or enhance vendor dependence, Stackable embraces a more innovative strategy. All data applications are designed to integrate effortlessly and can be added or removed with remarkable speed. Built on Kubernetes, it is capable of operating in any environment, whether on-premises or in the cloud. To initiate your first Stackable data platform, all you require is stackablectl along with a Kubernetes cluster. In just a few minutes, you will be poised to begin working with your data. You can set up your one-line startup command right here. Much like kubectl, stackablectl is tailored for seamless interaction with the Stackable Data Platform. Utilize this command line tool for deploying and managing stackable data applications on Kubernetes. With stackablectl, you have the ability to create, delete, and update components efficiently, ensuring a smooth operational experience for your data management needs. The versatility and ease of use make it an excellent choice for developers and data engineers alike.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Apache Airflow No 
Apache Druid No 
Apache HBase No 
Apache Hive No 
Apache Iceberg No 
Apache Kafka No 
Apache NiFi No 
Apache ZooKeeper No 
Docker No 
Git No 
Kubernetes No 
MinIO No 
OpenSearch No 
Prometheus No 
RadiantOne Yes 
Switch Automation Yes 
Trino No 

Integrations

Apache Spark Yes 
Apache Airflow Yes 
Apache Druid Yes 
Apache HBase Yes 
Apache Hive Yes 
Apache Iceberg Yes 
Apache Kafka Yes 
Apache NiFi Yes 
Apache ZooKeeper Yes 
Docker Yes 
Git Yes 
Kubernetes Yes 
MinIO Yes 
OpenSearch Yes 
Prometheus Yes 
RadiantOne No 
Switch Automation No 
Trino Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 Yes 
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 Yes 
Live Rep (24/7) Yes 
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 Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/analytics/ca/en/technology/cloud-data-services/spark-as-a-service/

Vendor Details

Company Name

Stackable

Founded

2020

Country

Germany

Website

stackable.tech/

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Integration

Dashboard No 
ETL - Extract / Transform / Load No 
Metadata Management No 
Multiple Data Sources No 
Web Services No 

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration Yes 
Data Quality Control No 
Data Security Yes 
Information Governance No 
Master Data Management No 
Match & Merge No 

Data Warehouse

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

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