Top Vertica Alternatives & Competitors For 2024

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.

QlikView is one of the foremost BI solutions in the market today, mainly due to the power of its associative query engine to link data from multiple sources that drives its visually impressive dashboards. With its strong data visualization capabilities, users can perform search and filter through data on-the-fly and conduct deep-dives to glean insights that matter to them. With a fast setup, users can have their first data model up and running in very little time. The software resides in-memory and houses data in RAM for quicker retrieval. With multi-tier access permissions for in-organization users, it enables users to view executive summaries at a glance, while allowing them to drill-down into data to find out more. Sadly, Qlik is now scaling back on improvements and updates for QlikView and focusing on promoting QlikSense instead, a possible reason why its filter and search functions, ad-hoc reporting and graphics are lagging in terms of quality, as mentioned in many user reviews. Also, this platform can prove to be resource-heavy for databases housed on local machines, especially when performing batch update jobs. In addition to inflexible pricing plans and the cost of licensing, quite a few necessary add-ons are paid. In summary, QlikView is one of the leading in-memory BI tools available in the market today and rates excellently with users in terms of data aggregation and visualization capabilities; however, buyers should factor in its pricing plans and other limitations when searching for the perfect BI solution for their enterprise.

Bigquery is a scalable big data warehouse solution. It enables users to pull correlated data streams using SQL like queries. Queries are executed fast regardless of the size of the datasets. It manages the dynamic distribution of workloads across computational clusters. The easy-to-navigate UI is robust and allows the user to create and execute machine learning models seamlessly. Users liked that it can connect to a variety of data analytics and visualization tools. However, users complained that query optimization is an additional hassle they have to deal with, as the solution is expensive and poorly constructed queries can quickly accumulate charges. It can be overwhelming for the non-technical user, and SQL coding knowledge is required to leverage its data analysis capabilities. Data visualization features are lacking and in need of improvement.

SAS Viya is an AI-powered data management and visual analytics platform with a robust, scalable architecture. All users who reviewed data source connectivity said that it connects to multiple sources and integrates easily with business applications, giving a seamless user experience. With fast in-memory processing of big data sets, it leverages the power of R to enable visual statistics. All users who mentioned predictive analysis said that it enables automated forecasting through what-if scenarios, goal-seeking, text mining and decision trees. Citing ease of use, all users say that the platform is intuitive and enables easy data modeling and self-service visual analytics. All users who mentioned support said that they are responsive and knowledgeable. Around 71% of the users who comment on its functionality say that it is a robust, scalable and flexible platform that enables visualization and analysis of business data, though some users say visual statistics need improvement. On the flip side, all users who review its cost say that the tool is expensive. In summary, SAS Viya is an analytics tool that provides data management, visualization and AI-powered analytics to enterprises for improved decision making, though small organizations and startups might find it cost-prohibitive.

User reviews of Amazon SageMaker reveal a platform appreciated for its robust feature set, scalability, and cost-efficiency. Many users find its comprehensive tools for data preprocessing, model training, deployment, and monitoring to be a significant strength. Scalability is another key advantage, with SageMaker accommodating both small-scale experiments and large-scale production workloads effectively. However, some users point out that SageMaker has a steep learning curve, particularly for beginners, and cost management can be challenging, especially during extensive model training. The platform's dependency on the broader AWS ecosystem can lead to vendor lock-in, which may not be ideal for organizations seeking flexibility. SageMaker's AutoML capabilities, such as Autopilot, are praised for automating complex tasks, but some advanced users note limitations in customization. Additionally, while designed for real-time inference, it may not be optimized for batch processing or offline use cases. In comparison to similar products, SageMaker stands out for its deep integration with AWS services, making it a preferred choice for those already within the AWS ecosystem. However, the learning curve and potential cost challenges are factors that users weigh against its benefits. The platform's active community support and extensive documentation receive positive mentions, contributing to a smoother user experience. Overall, Amazon SageMaker is a powerful tool for machine learning but requires careful consideration of its complexities and potential cost implications.