SAP HANA vs Vertica

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Our analysts compared SAP HANA vs Vertica based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

SAP HANA Software Tool
Vertica Software Tool

Product Basics

SAP HANA is the in-memory database for SAP’s Business Technology platform with strong data processing and analytics capabilities that reduce data redundancy and data footprint, while optimizing hardware and IT operational needs to support business in real time. Available on-premise, in the cloud and as a hybrid solution, it performs advanced analytics on live transactional data to display actionable information.

With an in-memory architecture and lean data model that helps businesses access data at the speed of thought, it serves as a single source of all relevant data. It integrates with a multitude of systems and databases, including geo-spatial mapping tools, to give businesses the insights to make KPI-focused decisions.
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Vertica is an analytics and data exploration platform designed to ingest massive quantities of data, parse it, and then return business insights as reports and interactive graphics. Elastically scalable, it provides batch as well as streaming analytics with massively parallel processing, ANSI-compliant SQL querying and ACID transactions.

Deployable in the cloud, on-premise, on Apache Hadoop and as a hybrid model, its resource manager enables concurrent job runs with reduced CPU and memory usage and data compression for storage optimization. A serverless setup and advanced data trawling techniques help users store and access their data with ease.
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$972/Capacity Unit, Usage-Based
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$3.19/Hour, Usage-Based
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Product Insights

  • Database Management: Reduces operational complexity through the use of a single database that allows data to be stored without a predefined structure. Provides data structure flexibility to application developers. Joins this data with many other data types with full interoperability. 
  • Build Business Solutions: The Business Function Library delivers pre-built functions that developers link at the database kernel level to build powerful business solutions. 
  • Geo-spatial Analysis: Stores spatial data and enables geographical data processing to drive location-specific business application development. 
  • Deploy Anywhere: Deploy on-premise, multi-cloud or go hybrid. Set up on traditional servers, pre-configured appliances, the HANA Enterprise Cloud or partner clouds including AWS and Microsoft Azure. Extend on-premise solutions to the cloud smoothly during any phase of the project. 
  • Predictive Analytics and Machine Learning: Supports transactional processing through machine learning and data analysis in real time. Take action before or as events happen to improve results and boost productivity. 
  • Smart Data Access: Connect virtually to remote, externally supported databases. Stores only the metadata of the database objects as a virtual table in the local database schema. Access data from the remote database in real time, irrespective of its location. 
  • Reduced Cost of Ownership: Mitigates hardware costs through a reduced data footprint made possible by a compression algorithm and lean data structure. 
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  • Improve Decision Making: Get business insights like workforce metrics, retail information, vital proprietary intel and usage data through data ingestion from diverse sources. Its high-level overview of diverse data pools empowers data-driven business decisions. 
  • Self-Service Analytics:  Provide self-service reporting and analysis for users of all skill levels — from non-technical users to analysts — at a more sophisticated level, using custom formulas and algorithms. 
  • Big Data Insights: Get intel and insights through large data silos to enrich business decisions and diagnose pain points or attach victories to actionable data. 
  • Gain a Competitive Advantage: Take on competitors and optimize business operations through data-informed decision-making. 
  • Flexible Licensing: Buy the product outright, purchase a subscription or pay by the hour with its flexible licensing. Hourly usage comes with full support and requires no commitment. 
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  • Data Integration: Captures any type of data — structured or unstructured — from database transactions, applications and streaming data sources. Ingests part of a data set or the complete data set into its native architecture for ready access. 
  • Capture and Replay: Record complex database transactions and then replay them on another device. Test on a non-production system while using production transactions, on a hosted instance, or in the cloud. 
  • Graph Data Processing: Combines its built-in graph engine with the in-memory relational database. Makes graph processing of relational tables easy to learn and use. 
  • SAP HANA Cockpit: Configure and manage HANA instances and applications through a single console interface. Easily schedule all backup jobs and monitor the system for immediate visibility of potential blockers. Integrate with other applications for workload management and security. 
  • Flexible Querying: Choose from a variety of semantics structures to query data in the database memory through a flexible algorithm. 
  • In-memory Architecture: Analyze insights in real time to monitor business KPIs and generate forecast trends. Access data quicker than with conventional databases via its in-memory database. 
  • Data Compression: Compresses data by up to 11 times and stores it in columnar structures for high-performance read and write operations. Saves storage space and provides faster data access for search and complex calculations. 
  • Parallel Processing: Performs basic calculations, such as joins, scans and aggregations in parallel, leveraging column-based data structures. Processes data quicker for distributed systems. 
  • Real-time Analysis: Queries transactional data directly as it is added in real-time. Leverages its inbuilt data processing algorithm to read and write data to a column storage table at high speeds. Acquire total visibility over information while it is being analyzed and make on-the-spot, incisive decisions. 
  • Role-based Permissions: Maintain data integrity across the organization — assign data access based on each team member’s role. 
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  • Streaming Analytics: Connects to Apache Kafka for IoT data analysis in real time. Analyzes and manages large volumes of data from IoT devices such as machine and sensor data for buildings, vehicles, medical systems, smart devices and wearables. 
  • Machine Learning: Get automated insights and deliverables through machine learning modules that automatically digest and parse large data portions. ML modules are built into its core — no need to pay for them or install them separately. 
  • Software Only: Work with a robust software interface with dedicated IT resources. All data warehousing, storage and processing infrastructure is hosted offsite. 
  • Fast SQL Databases: Store and retrieve data through highly scalable and speedy SQL databases. 
  • Massively Parallel Processing: Get increased speed and scalability at larger scales by running two processes side-by-side through massively parallel processing. 
  • Columnar Storage: Read only the most important sets of data first through columnar storage that greatly speeds up data retrieval. 
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Product Ranking

#13

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Big Data Analytics Tools

#31

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Big Data Analytics Tools

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User Sentiment Summary

Great User Sentiment 1173 reviews
Great User Sentiment 203 reviews
86%
of users recommend this product

SAP HANA has a 'great' User Satisfaction Rating of 86% when considering 1173 user reviews from 4 recognized software review sites.

88%
of users recommend this product

Vertica has a 'great' User Satisfaction Rating of 88% when considering 203 user reviews from 3 recognized software review sites.

4.2 (345)
4.5 (108)
4.6 (19)
n/a
4.3 (328)
4.3 (65)
4.3 (481)
4.2 (30)

Synopsis of User Ratings and Reviews

Data Analysis: Around 92% of users who reviewed data analysis said that the tool analyzes and displays insights and trend forecasts of transactional data in real time to enable timely decision-making.
Data Processing: Approximately 91% of the users who discussed data processing said that the tool can query large amounts of data due to its in-memory architecture and data compression algorithm.
Data Integration: Around 87% of the users said that the solution migrates data efficiently from a wide range of SAP and non-SAP systems.
Support: Approximately 87% of the users who discussed support said that they are responsive, and online user communities and knowledge bases assist in faster resolution of issues.
Speed and Performance: Citing the tool’s fast runtime, around 76% of the users said that they can perform on-the-fly calculations at very high speeds.
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Data Processing: All users who mention computing say that the tool’s columnar storage and parallel processing enable faster querying.
Performance: Almost 72% of the users who review performance say the platform is robust and reliable with high availability.
Functionality: Around 56% of the users who review functionality say that it is feature-rich and performs as expected.
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Pricing: Approximately 80% of the users who mentioned pricing said that the solution’s in-memory architecture demands large amounts of RAM, which adds to the cost.
Functionality: According to around 53% of the users who reviewed functionality, the solution needs to be more flexible and agile to perform complex calculations on large datasets.
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Cost: All users who mention cost say that data storage limits can be restrictive and the tool is expensive.
Community Support: Citing lack of technical community support, approximately 50% of the users say that it makes adoption difficult.
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SAP HANA is a multi-model database and analytics platform that combines real-time transactional data with predictive analytics and machine learning capabilities to drive business decisions quicker. Most of the users who mentioned analytics said that, with its Online Analytical Processing(OLAP) and Online Transactional Processing(OLTP) capabilities, the tool analyzes data faster with predictive modeling and machine learning. Many users who reviewed data processing said that the tool has a lean data model due to its in-memory architecture and columnar storage capabilities, and, paired with its compression algorithm, can perform calculations on-the-fly on huge volumes of data. In reference to data integration, many users said that the platform connects seamlessly with both SAP and non-SAP systems, such as mapping tools like ArcGIS, to migrate data to a consolidated repository, though quite a few users said that integration with media files and Google APIs is tedious. Most of the users who reviewed support said that they are responsive, and online user communities and documentation help in resolving issues, whereas some users said that the support reps had limited knowledge. A majority of the users who reviewed its speed said that the platform has a fast runtime, though some users said that it requires high-performing hardware infrastructure to do so and that memory management might be tricky with large datasets. The software does have its limitations though. Being in-memory, the tool is RAM-intensive, which can add to the cost of ownership, though some users said that data compression reduces the database size and saves on hardware cost. A majority of the users who reviewed its functionality said that it needs to be more mature in terms of flexibility and agility, though some users said that with easy updates and maintenance, it is a robust solution and increases efficiency and productivity. In summary, SAP HANA serves as a single source of truth for analysis of large volumes of data and uncovering consumer insights through planning, forecasting and drill-down reporting. However, it seems more suited for large organizations with complex data types and analytics workflows because of its costly pricing plans.

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Vertica Analytics is a big data relational database that provides batch as well as streaming analytics to enterprises. Citing a robust, distributed architecture with massively parallel processing (MPP), all users who review data processing say that it performs extremely fast computing with I/O optimization, and columnar storage makes it ideal for reporting. Approximately 72% of the users who review performance say that it is a reliable tool with high availability and virtually no downtime, with K-safety protocol in place for efficient fault tolerance. Citing its feature set, around 56% of the users say that they are satisfied with its elastic scalability, rich analytical functions and excellent clustering technology. On the flip side, almost 50% of the users who mention technical and community support say that it is inadequate and possibly contributes to the platform’s steep learning curve. All users who review its cost say that the solution is expensive, with restrictive data storage limits. In summary, Vertica is a big data and analytics platform that provides streaming analytics with lightning-fast query speeds, machine learning and forecast capabilities.

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