Event stream processing (ESP) is a technology that enables organizations to analyze and act on real-time data streams in order to make timely and informed decisions. With the increasing volume and velocity of data being generated in today’s digital world, ESP has become a critical tool for businesses looking to stay competitive.
In this blog post, we will explore statistics on ESP, including trends, adoption, market analysis, and demographics.
Key Event stream processing (ESP) Statistics 2023 – MY Choice
- The global event stream processing market is expected to reach $11.9 billion by 2027, growing at a CAGR of 18.1% from 2020 to 2027.
- The use of event stream processing in the financial services industry is expected to grow at a CAGR of 24.2% from 2020 to 2025.
- The retail and e-commerce industry is also expected to see significant growth in the use of event stream processing, with a CAGR of 23.2% from 2020 to 2025.
- Real-time fraud detection and prevention is the most popular use case for event stream processing, accounting for over 35% of the market share.
- The Asia-Pacific region is expected to see the highest growth in the event stream processing market, with a CAGR of 21.8% from 2020 to 2025.
- The use of cloud-based event stream processing solutions is expected to grow at a CAGR of 22.8% from 2020 to 2025.
- The use of event stream processing in the healthcare and life sciences industry is expected to grow at a CAGR of 22.1% from 2020 to 2025.
- The use of event stream processing in the manufacturing industry is expected to grow at a CAGR of 21.7% from 2020 to 2025.
- The use of event stream processing in the energy and utilities industry is expected to grow at a CAGR of 20.9% from 2020 to 2025.
- By 2025, the event stream processing market is expected to have a compound annual growth rate (CAGR) of 23.2%.
Event stream processing (ESP) Trends
- The global event stream processing market is expected to reach $11.1 billion by 2025, growing at a CAGR of 22.9% from 2020 to 2025.
- The use of ESP in the financial services industry is projected to grow at a CAGR of 30.5% during the forecast period 2020-2025.
- The adoption of ESP in the manufacturing industry is expected to increase at a CAGR of 25.2% during the forecast period 2020-2025.
- The healthcare and life sciences industry is expected to witness a CAGR of 23.9% during the forecast period 2020-2025.
- The retail and e-commerce industry is expected to witness a CAGR of 22.7% during the forecast period 2020-2025.
Event stream processing (ESP) Adoption
- More than 60% of organizations are using or planning to use ESP in the next 12 months.
- The adoption rate of ESP in North America is expected to be the highest during the forecast period 2020-2025.
- The adoption rate of ESP in Asia Pacific is expected to be the second highest during the forecast period 2020-2025.
- The adoption rate of ESP in Europe is expected to be the third highest during the forecast period 2020-2025.
- The adoption rate of ESP in Latin America is expected to be the fourth highest during the forecast period 2020-2025.
Event stream processing (ESP) Market Analysis
- The North American market for ESP is expected to hold the largest share of the global market during the forecast period 2020-2025.
- The Asia Pacific market for ESP is expected to grow at the highest CAGR during the forecast period 2020-2025.
- The Europe market for ESP is expected to hold the second-largest share of the global market during the forecast period 2020-2025.
- The Latin America market for ESP is expected to grow at the third-highest CAGR during the forecast period 2020-2025.
- The Middle East and Africa market for ESP is expected to grow at the fourth-highest CAGR during the forecast period 2020-2025.
Event stream processing (ESP) Demographics
- The small and medium-sized enterprise (SME) segment is expected to grow at the highest CAGR during the forecast period 2020-2025.
- The large enterprise segment is expected to hold the largest share of the global market during the forecast period 2020-2025.
- The ESP market by vertical is segmented into BFSI, healthcare, retail and e-commerce, manufacturing, and others.
- The BFSI vertical is expected to hold the largest share of the global market during the forecast period 2020-2025.
- The healthcare vertical is expected to grow at the highest CAGR during the forecast period 2020-2025.
Event Stream Processing Market Statistics
- The Event Stream Processing market is anticipated to witness a CAGR of 20.6% over the forecast period 2021.
Event Stream Processing Latest Statistics
- Without the deduplication logic, the discrepancies are already small, with an average of 0.05% for all metrics.
- The deduplication logic helps reduce the discrepancies to be negligible, with an average of 0.003%, meaning we only produce 3 incorrect counts for every 100,000 events.
- Since fetching information and opcodes to those few ALUs is expensive, very little die area is dedicated to actual mathematical machinery (as a rough estimation, consider it to be less than 10%).
- Most (90%).
- If an iterator’s age passes 50% of theretention period , there is risk for data loss due to record expiration.
- Asia Pacific Largest Market North America CAGR 20.6 % Market Overview.
- Consumer Technology Association estimated that Consumer Electronics Shipments in the U.S. could contribute to USD 301 billion of wholesale revenue, for the year 2019.
- According to Eurostat, the statistics pertaining to online banking indicated that about 58% of the EU population used internet banking in 2019.
- The Event Stream Processing Market is growing at a CAGR of 20.6% over the next 5 years.
- Wix works with Google Cloud to offer user dashboards that cut dev costs by 20%.
- For each dataset, we randomly selected 90% streams for training, and the remaining 10% for testing.
- Our classifier plateaus around 100% accuracy for PokerDVS and Posture DVS, which only contains 4 and 3 different categories with sufficient number of training segments.
- The accuracy on MNISTDVS is a bit lower than 80%, as it has as many as 10 different digits to be classified, but only with approximately the same number of training segments as Posture.
- Not surprisingly, the accuracy on CIFAR10 DVS reaches only 30%.
- In each validation fold, 90% data of one AER set were randomly picked out for training and the other 10% for classification testing.
- To further demonstrate the hardware friendliness of our framework, Table 3 compares the performance of the estimated hardware random ferns and an online learning hardware SVM [33].
- According to the routine of Xilinx FPGA devices, one DSP48E module is used as one multiplier, and one BRAM module is a memory block with 4KB capacity in Table 3.
- Under the training rate of 90% as mentioned above, there are 19992, 467, 22175, 111850 training segments and 10, 4, 3, 10 classes for the 4 AER datasets, respectively.
- In the first cycle, corresponding N*.
- As a managed service, Stream Analytics guarantees event processing with a 99.9% availability at a minute level of granularity.