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Gigaspaces Smart Cache vs IBM Streams comparison

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Gigaspaces Smart Cache

105 views|81 comparisons
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IBM Streams

Read 5 IBM Streams reviews
674 views|593 comparisons
100% willing to recommend
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Buyer's Guide
Streaming Analytics
April 2024
Executive Summary

We performed a comparison between Gigaspaces Smart Cache and IBM Streams based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics.
To learn more, read our detailed Streaming Analytics Report (Updated: April 2024).
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768,886 professionals have used our research since 2012.
Featured Review
Use Gigaspaces Smart Cache?
Ahmed_Emad
A solution for data pipelines but has connector limitations
Quick deployments
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What is your experience regarding pricing and costs for IBM Streams?
Top Answer:The solution’s licenses pricing is different from one region to another region. I rate the solution’s pricing a seven out of ten.
What needs improvement with IBM Streams?
Top Answer:the limited number of connectors. This shall be overcome with work-arounds or eventually buying additional connectors to complete the solution.
What is your primary use case for IBM Streams?
Top Answer:We use the solution for data pipeline by modernizing the traditional ETL jobs done through advanced streaming. Another use case is building the g2g streaming platform, which facilitates data exchange… more »
Ranking
31st
out of 38 in Streaming Analytics
Views
105
Comparisons
81
Reviews
0
Average Words per Review
0
Rating
N/A
15th
out of 38 in Streaming Analytics
Views
674
Comparisons
593
Reviews
1
Average Words per Review
447
Rating
7.0
Comparisons
Also Known As
Gigaspaces InsightEdge
IBM InfoSphere Streams
Learn More
GigaSpaces
IBM
Overview

Smart Cache is the fastest, most scalable, distributed caching tier that runs on any operational data source, to accelerate your digital applications and fuel real-time reporting and BI. Smart Cache is optimized for rapidly changing data and multi-criteria queries; and is fully SQL compatible.

IBM Streams is an advanced analytic platform that allows user-developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of data stream sources. The solution can handle very high data throughput rates, up to millions of events or messages per second. Streams helps you analyze data in motion, simplify development of streaming applications, and extend the value of existing systems.
Sample Customers
UBS, Daiwa Capital Markets, Morgan Stanley, Schneider Electric, Frequentis, SG Digital, Charles Schwab, 888 Holdings, BNP Paribas, Liberty Global
Globo TV, All England Lawn Tennis Club, CenterPoint Energy, Consolidated Communications Holdings, Darwin Ecosystem, Emory University Hospital, ICICI Securities, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Living Roads, Mobileum, Optibus, Southern Ontario Smart Computing Innovation Platform (SOSCIP), University of Alberta, University of Montana, University of Ontario Institute of Technology, Wimbledon 2015
Top Industries
No Data Available
VISITORS READING REVIEWS
Financial Services Firm24%
Computer Software Company15%
Comms Service Provider6%
Real Estate/Law Firm5%
Company Size
No Data Available
VISITORS READING REVIEWS
Small Business18%
Midsize Enterprise10%
Large Enterprise72%
Buyer's Guide
Streaming Analytics
April 2024
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Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Confluent and others in Streaming Analytics. Updated: April 2024.
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768,886 professionals have used our research since 2012.

Gigaspaces Smart Cache is ranked 31st in Streaming Analytics while IBM Streams is ranked 15th in Streaming Analytics with 5 reviews. Gigaspaces Smart Cache is rated 0.0, while IBM Streams is rated 8.2. On the other hand, the top reviewer of IBM Streams writes "A solution for data pipelines but has connector limitations". Gigaspaces Smart Cache is most compared with , whereas IBM Streams is most compared with Confluent, Azure Stream Analytics, Apache Flink, Apache Spark and Apache NiFi.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.