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What is Spark?

Digital contracts that are seamlessly integrated into your CRM and marketing tools enhance your sales and marketing operations by providing a unified login, thereby removing the complexities of managing several platforms. Specifically designed for the real estate industry, Spark equips your team to oversee the entire sales process, from managing inventory to generating contracts. Given that each developer has distinct criteria for assessing contacts and that team configurations can differ significantly, Spark offers customizable solutions that adapt to your specific workflow while maintaining operational continuity. Whether your focus is on condos, townhomes, master-planned developments, single-family residences, or apartments, Spark delivers a comprehensive platform essential for the selling, marketing, closing, and reporting of your diverse new development projects. Our dedication starts with a deep understanding of your objectives, ensuring that the platform aligns with your team's preferences and the distinct needs of your local market. The consultative process kicks off with the creation of a tailored onboarding and training plan that actively involves your whole team, promoting a spirit of collaboration for achieving success. This customized strategy guarantees that Spark not only addresses your existing demands but also adapts as your business evolves over time, allowing for continuous growth and improvement. Ultimately, this level of personalization makes Spark an invaluable asset in navigating the complexities of real estate transactions.

What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

Media

Media

Integrations Supported

Algonomy
Datameer
Mage Dynamic Data Masking
Mage Static Data Masking
Acceldata
Apache Atlas
Apache Sentry
Causal
Data Sentinel
Fosfor Decision Cloud
IBM Cloud Pak for Integration
IBM watsonx.data
IRI Voracity
QueryPie
Rational BI
StreamFlux
Union Cloud
e6data
jethro

Integrations Supported

Algonomy
Datameer
Mage Dynamic Data Masking
Mage Static Data Masking
Acceldata
Apache Atlas
Apache Sentry
Causal
Data Sentinel
Fosfor Decision Cloud
IBM Cloud Pak for Integration
IBM watsonx.data
IRI Voracity
QueryPie
Rational BI
StreamFlux
Union Cloud
e6data
jethro

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Spark RE Technologies

Date Founded

2013

Company Location

Canada

Company Website

spark.re

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

Real Estate Agency

Calendar Management
Client / Property Matching
Client Database
Commission Management
Contact Management
Contract Management
Email Marketing
Flyer / Catalog Printing
Lead Management
Listing Management
Property Database
Website Management

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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