164 Integrations with Apache Spark
View a list of Apache Spark integrations and software that integrates with Apache Spark below. Compare the best Apache Spark integrations as well as features, ratings, user reviews, and pricing of software that integrates with Apache Spark. Here are the current Apache Spark integrations in 2024:
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1
Vertex AI
Google
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection. -
2
Scalytics Connect
Scalytics
Scalytics Connect enables AI and ML to process and analyze data, makes it easier and more secure to use different data processing platforms at the same time. Built by the inventors of Apache Wayang, Scalytics Connect is the most enhanced data management platform, reducing the complexity of ETL data pipelines dramatically. Scalytics Connect is a data management and ETL platform that helps organizations unlock the power of their data, regardless of where it resides. It empowers businesses to break down data silos, simplify access, and gain valuable insights through a variety of features, including: - AI-powered ETL: Automates tasks like data extraction, transformation, and loading, freeing up your resources for more strategic work. - Unified Data Landscape: Breaks down data silos and provides a holistic view of all your data, regardless of its location or format. - Effortless Scaling: Handles growing data volumes with ease, so you never get bottlenecked by information overloadStarting Price: $0 -
3
Kubernetes
Kubernetes
Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes builds upon 15 years of experience of running production workloads at Google, combined with best-of-breed ideas and practices from the community. Designed on the same principles that allows Google to run billions of containers a week, Kubernetes can scale without increasing your ops team. Whether testing locally or running a global enterprise, Kubernetes flexibility grows with you to deliver your applications consistently and easily no matter how complex your need is. Kubernetes is open source giving you the freedom to take advantage of on-premises, hybrid, or public cloud infrastructure, letting you effortlessly move workloads to where it matters to you.Starting Price: Free -
4
Sematext Cloud
Sematext Group
Sematext Cloud is an innovative, unified platform with all-in-one solution for infrastructure monitoring, application performance monitoring, log management, real user monitoring, and synthetic monitoring to provide unified, real-time observability of your entire technology stack. It's used by organizations of all sizes and across a wide range of industries, with the goal of driving collaboration between engineering and business teams, reducing the time of root-cause analysis, understanding user behaviour and tracking key business metrics. The main capabilities range from log monitoring to APM, server monitoring, database monitoring, network monitoring, uptime monitoring, website monitoring or container monitoring Find complete details on our website. Or better: start a free demo, no email address required.Starting Price: $0 -
5
Jupyter Notebook
Project Jupyter
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. -
6
Amazon EC2
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 delivers the broadest choice of compute, networking (up to 400 Gbps), and storage services purpose-built to optimize price performance for ML projects. Build, test, and sign on-demand macOS workloads. Access environments in minutes, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing. Access the on-demand infrastructure and capacity you need to run HPC applications faster and cost-effectively. Amazon EC2 delivers secure, reliable, high-performance, and cost-effective compute infrastructure to meet demanding business needs. -
7
SingleStore
SingleStore
SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.Starting Price: $0.69 per hour -
8
Apache Cassandra
Apache Software Foundation
The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages. -
9
Dataiku DSS
Dataiku
Bring data analysts, engineers, and scientists together. Enable self-service analytics and operationalize machine learning. Get results today and build for tomorrow. Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) or a customizable drag-and-drop visual interface at any step of the predictive dataflow prototyping process – from wrangling to analysis to modeling. Profile the data visually at every step of the analysis. Interactively explore and chart your data using 25+ built-in charts. Prepare, enrich, blend, and clean data using 80+ built-in functions. Leverage Machine Learning technologies (Scikit-Learn, MLlib, TensorFlow, Keras, etc.) in a visual UI. Build & optimize models in Python or R and integrate any external ML library through code APIs. -
10
JupyterLab
Jupyter
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible, configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular, write plugins that add new components and integrate with existing ones. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include, data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala. -
11
Apache Hive
Apache Software Foundation
The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API. -
12
LogIsland
Hurence
The LogIsland platform is at the heart of Hurence’s real-time analytics. It allows you to capture factory events (IIoT) but also events from your websites. According to Hurence a factory, or more generally a company, can be understood and supervised in real time through all the events it encounters: a sales order is an event, the production of a piece by a robot is an event, the delivery of a product is an event. Everything is actually an event. The LogIsland platform allows you to capture all these events, put them in a message bus for large volumes and analyze them in real time with plug and play analyzers ranging from simple (counting, alerts, recommendations), to the most sophisticated: artificial intelligence models for predictions and detection of anomalies or defects. Your Swiss knife for analyzing events in real time with custom analyzers for two verticals, web analytics and industry 4.0. -
13
Activeeon ProActive
Activeeon
The solution provided by Activeeon is suited to fit modern challenges such as the growth of data, new infrastructures, cloud strategy evolving, new application architecture, etc. It provides orchestration and scheduling to automate and build a solid base for future growth. ProActive Workflows & Scheduling is a java-based cross-platform workflow scheduler and resource manager that is able to run workflow tasks in multiple languages and multiple environments (Windows, Linux, Mac, Unix, etc). ProActive Resource Manager makes compute resources available for task execution. It handles on-premises and cloud compute resources in an elastic, on-demand and distributed fashion. ProActive AI Orchestration from Activeeon empowers data engineers and data scientists with a simple, portable and scalable solution for machine learning pipelines. It provides pre-built and customizable tasks that enable automation within the machine learning lifecycle, which helps data scientists and IT Operations work.Starting Price: $10,000 -
14
Dagster+
Dagster Labs
Dagster is a next-generation orchestration platform for the development, production, and observation of data assets. Unlike other data orchestration solutions, Dagster provides you with an end-to-end development lifecycle. Dagster gives you control over your disparate data tools and empowers you to build, test, deploy, run, and iterate on your data pipelines. It makes you and your data teams more productive, your operations more robust, and puts you in complete control of your data processes as you scale. Dagster brings a declarative approach to the engineering of data pipelines. Your team defines the data assets required, quickly assessing their status and resolving any discrepancies. An assets-based model is clearer than a tasks-based one and becomes a unifying abstraction across the whole workflow.Starting Price: $0 -
15
Union Cloud
Union.ai
Union.ai is an award-winning, Flyte-based data and ML orchestrator for scalable, reproducible ML pipelines. With Union.ai, you can write your code locally and easily deploy pipelines to remote Kubernetes clusters. “Flyte’s scalability, data lineage, and caching capabilities enable us to train hundreds of models on petabytes of geospatial data, giving us an edge in our business.” — Arno, CTO at Blackshark.ai “With Flyte, we want to give the power back to biologists. We want to stand up something that they can play around with different parameters for their models because not every … parameter is fixed. We want to make sure we are giving them the power to run the analyses.” — Krishna Yeramsetty, Principal Data Scientist at Infinome “Flyte plays a vital role as a key component of Gojek's ML Platform by providing exactly that." — Pradithya Aria Pura, Principal Engineer at GojStarting Price: Free (Flyte) -
16
Style Intelligence
InetSoft
Style Intelligence by InetSoft is a complete business intelligence (BI) software platform that empowers companies to explore, analyze, monitor, report, and collaborate on critical business and operational data from disparate sources in real time. Its top features include a real-time data mashup Data Block architecture, professional atomic data block modeling tool, and database write-back option. Robust and easy to use, Style Intelligence is also fully scalable and offers granular security, multi-tenancy support, and multiple integrations. InetSoft's cloud flexible business intelligence solution delivers the benefit of cloud computing and software-as-a-service while giving you the maximum level of control. In terms of software-as-a-service, BI software is unique because it inherently depends on the data not being embedded in the application. InetSoft provides free expert fast-start mentoring that delivers the expertise even when no in-house dedicated BI expert is available.Starting Price: $165/month -
17
Instaclustr
Instaclustr
Instaclustr is the Open Source-as-a-Service company, delivering reliability at scale. We operate an automated, proven, and trusted managed environment, providing database, analytics, search, and messaging. We enable companies to focus internal development and operational resources on building cutting edge customer-facing applications. Instaclustr works with cloud providers including AWS, Heroku, Azure, IBM Cloud, and Google Cloud Platform. The company has SOC 2 certification and provides 24/7 customer support.Starting Price: $20 per node per month -
18
Alluxio
Alluxio
Alluxio is world’s first open source data orchestration technology for analytics and AI for the cloud. It bridges the gap between data driven applications and storage systems, bringing data from the storage tier closer to the data driven applications and makes it easily accessible enabling applications to connect to numerous storage systems through a common interface. Alluxio’s memory-first tiered architecture enables data access at speeds orders of magnitude faster than existing solutions. Imagine as an IT leader having the flexibility to choose any services that are available in public cloud and on premises. And imagine being able to scale your storage for your data lakes with control over data locality and protection for your organization. With these goals in mind, NetApp and Alluxio are joining forces to help our customers adapt to new requirements for modernizing data architecture with low-touch operations for analytics, machine learning, and artificial intelligence workflows.Starting Price: 26¢ Per SW Instance Per Hour -
19
Solace PubSub+
Solace
Solace PubSub+ Platform helps enterprises design, deploy and manage event-driven systems across hybrid and multi-cloud and IoT environments so they can be more event-driven and operate in real-time. The PubSub+ Platform includes the powerful PubSub+ Event Brokers, event management capabilities with PubSub+ Event Portal, as well as monitoring and integration capabilities all available via a single cloud console. PubSub+ allows easy creation of an event mesh, an interconnected network of event brokers, allowing for seamless and dynamic data movement across highly distributed network environments. PubSub+ Event Brokers can be deployed as fully managed cloud services, self-managed software in private cloud or on-premises environments, or as turnkey hardware appliances for unparalleled performance and low TCO. PubSub+ Event Portal is a complimentary toolset for design and governance of event-driven systems including both Solace and Kafka-based event broker environments. -
20
Coginiti
Coginiti
Coginiti, the AI-enabled enterprise data workspace, empowers everyone to get consistent answers fast to any business question. Accelerating the analytic development lifecycle from development to certification, Coginiti makes it easy for you to search and find approved metrics for your use case. Coginiti integrates all the functionality you need to build, approve, version, and curate analytics across all business domains for reuse, all while adhering to your data governance policy and standards. Data and analytic teams in the insurance, financial services, healthcare, and retail/consumer package goods industries trust Coginiti’s collaborative data workspace to deliver value to their customers.Starting Price: $189/user/year -
21
Riak TS
Riak
Riak® TS is the only enterprise-grade NoSQL time series database optimized specifically for IoT and Time Series data. It ingests, transforms, stores, and analyzes massive amounts of time series data. Riak TS is engineered to be faster than Cassandra. The Riak TS masterless architecture is designed to read and write data even in the event of hardware failures or network partitions. Data is evenly distributed across the Riak ring and, by default, there are three replicas of your data. This ensures at least one copy of your data is available for read operations. Riak TS is a distributed system with no central coordinator. It is easy to set up and operate. The masterless architecture makes it easy to add and remove nodes from a cluster. The masterless architecture of Riak TS makes it easy to add and remove nodes from your cluster. You can achieve predictable and near-linear scale by adding nodes using commodity hardware.Starting Price: $0 -
22
IBM Analytics Engine provides an architecture for Hadoop clusters that decouples the compute and storage tiers. Instead of a permanent cluster formed of dual-purpose nodes, the Analytics Engine allows users to store data in an object storage layer such as IBM Cloud Object Storage and spins up clusters of computing notes when needed. Separating compute from storage helps to transform the flexibility, scalability and maintainability of big data analytics platforms. Build on an ODPi compliant stack with pioneering data science tools with the broader Apache Hadoop and Apache Spark ecosystem. Define clusters based on your application's requirements. Choose the appropriate software pack, version, and size of the cluster. Use as long as required and delete as soon as an application finishes jobs. Configure clusters with third-party analytics libraries and packages. Deploy workloads from IBM Cloud services like machine learning.Starting Price: $0.014 per hour
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23
Flyte
Union.ai
The workflow automation platform for complex, mission-critical data and ML processes at scale. Flyte makes it easy to create concurrent, scalable, and maintainable workflows for machine learning and data processing. Flyte is used in production at Lyft, Spotify, Freenome, and others. At Lyft, Flyte has been serving production model training and data processing for over four years, becoming the de-facto platform for teams like pricing, locations, ETA, mapping, autonomous, and more. In fact, Flyte manages over 10,000 unique workflows at Lyft, totaling over 1,000,000 executions every month, 20 million tasks, and 40 million containers. Flyte has been battle-tested at Lyft, Spotify, Freenome, and others. It is entirely open-source with an Apache 2.0 license under the Linux Foundation with a cross-industry overseeing committee. Configuring machine learning and data workflows can get complex and error-prone with YAML.Starting Price: Free -
24
Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
25
DQOps
DQOps
DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors. The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors. DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.Starting Price: $499 per month -
26
ZenML
ZenML
Simplify your MLOps pipelines. Manage, deploy, and scale on any infrastructure with ZenML. ZenML is completely free and open-source. See the magic with just two simple commands. Set up ZenML in a matter of minutes, and start with all the tools you already use. ZenML standard interfaces ensure that your tools work together seamlessly. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code. Write portable ML code and switch from experimentation to production in seconds. Manage all your favorite MLOps tools in one place with ZenML's plug-and-play integrations. Prevent vendor lock-in by writing extensible, tooling-agnostic, and infrastructure-agnostic code.Starting Price: Free -
27
Apache Iceberg
Apache Software Foundation
Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time. Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes. Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates. Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically. No extra filters are needed for fast queries, and the table layout can be updated as data or queries change.Starting Price: Free -
28
Protegrity
Protegrity
Our platform allows businesses to use data—including its application in advanced analytics, machine learning, and AI—to do great things without worrying about putting customers, employees, or intellectual property at risk. The Protegrity Data Protection Platform doesn't just secure data—it simultaneously classifies and discovers data while protecting it. You can't protect what you don't know you have. Our platform first classifies data, allowing users to categorize the type of data that can mostly be in the public domain. With those classifications established, the platform then leverages machine learning algorithms to discover that type of data. Classification and discovery finds the data that needs to be protected. Whether encrypting, tokenizing, or applying privacy methods, the platform secures the data behind the many operational systems that drive the day-to-day functions of business, as well as the analytical systems behind decision-making. -
29
RazorThink
RazorThink
RZT aiOS offers all of the benefits of a unified artificial intelligence platform and more, because it's not just a platform — it's a comprehensive Operating System that fully connects, manages and unifies all of your AI initiatives. And, AI developers now can do in days what used to take them months, because aiOS process management dramatically increases the productivity of AI teams. This Operating System offers an intuitive environment for AI development, letting you visually build models, explore data, create processing pipelines, run experiments, and view analytics. What's more is that you can do it all even without advanced software engineering skills. -
30
Querona
YouNeedIT
We make BI & Big Data analytics work easier and faster. Our goal is to empower business users and make always-busy business and heavily loaded BI specialists less dependent on each other when solving data-driven business problems. If you have ever experienced a lack of data you needed, time to consuming report generation or long queue to your BI expert, consider Querona. Querona uses a built-in Big Data engine to handle growing data volumes. Repeatable queries can be cached or calculated in advance. Optimization needs less effort as Querona automatically suggests query improvements. Querona empowers business analysts and data scientists by putting self-service in their hands. They can easily discover and prototype data models, add new data sources, experiment with query optimization and dig in raw data. Less IT is needed. Now users can get live data no matter where it is stored. If databases are too busy to be queried live, Querona will cache the data. -
31
Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.Starting Price: $5.00/Terabyte-Month
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32
PHEMI Health DataLab
PHEMI Systems
The PHEMI Trustworthy Health DataLab is a unique, cloud-based, integrated big data management system that allows healthcare organizations to enhance innovation and generate value from healthcare data by simplifying the ingestion and de-identification of data with NSA/military-grade governance, privacy, and security built-in. Conventional products simply lock down data, PHEMI goes further, solving privacy and security challenges and addressing the urgent need to secure, govern, curate, and control access to privacy-sensitive personal healthcare information (PHI). This improves data sharing and collaboration inside and outside of an enterprise—without compromising the privacy of sensitive information or increasing administrative burden. PHEMI Trustworthy Health DataLab can scale to any size of organization, is easy to deploy and manage, connects to hundreds of data sources, and integrates with popular data science and business analysis tools. -
33
Rational BI
Rational BI
Spend less time preparing your data and more time analyzing it. Not only can you build better looking and more accurate reports, you can centralize all your data gathering, analytics and data science in a single interface, accessible to everyone in the organization. Import all your data no matter where it lives. Whether you’re looking to build scheduled reports from your Excel files, cross-reference data between files and databases or turn your data into SQL queryable databases, Rational BI gives you all the tools you need. Discover the signals hidden in your data, make it available without delay and move ahead of your competition. Magnify the analytics capabilities of your organization through business intelligence that makes it easy to find the latest up-to-date data and analyze it through an interface that delights both data scientists and casual data consumers.Starting Price: $129 per month -
34
Azure Data Science Virtual Machines
Microsoft
DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.Starting Price: $0.005 -
35
Xtendlabs
Xtendlabs
Installing, and configuring today’s complex software technology platforms takes an extraordinary investment in time and resources. Not with Xtendlabs. Xtendlabs Emerging Technology Platform-as-a-Services provides immediate access to emerging Big Data, Data Sciences, and Database technology platforms online, from any device and location, 24/7. Xtendlabs are available on-demand, any time, from any location, including home, office or the road. Xtendlabs scale to meet your needs on-demand, so you can focus on your business problem and learning rather than struggling to find and set up infrastructure . Just sign-in to get immediate access to your virtual lab environment. Xtendlabs requires no virtual machine installation, system setup or configuration, saving valuable time and resources. Pay as you go monthly. With Xtendlabs there are no upfront investments in software or hardware. -
36
Warp 10
SenX
Warp 10 is a modular open source platform that collects, stores, and analyzes data from sensors. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 is both a time series database and a powerful analytics environment, allowing you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The analysis environment can be implemented within a large ecosystem of software components such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. It can also access data stored in many existing solutions, relational or NoSQL databases, search engines and S3 type object storage system. -
37
Prophecy
Prophecy
Prophecy enables many more users - including visual ETL developers and Data Analysts. All you need to do is point-and-click and write a few SQL expressions to create your pipelines. As you use the Low-Code designer to build your workflows - you are developing high quality, readable code for Spark and Airflow that is committed to your Git. Prophecy gives you a gem builder - for you to quickly develop and rollout your own Frameworks. Examples are Data Quality, Encryption, new Sources and Targets that extend the built-in ones. Prophecy provides best practices and infrastructure as managed services – making your life and operations simple! With Prophecy, your workflows are high performance and use scale-out performance & scalability of the cloud.Starting Price: $299 per month -
38
BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
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The single development environment for the entire data science workflow. Natively analyze your data with a reduction in context switching between services. Data to training at scale. Build and train models 5X faster, compared to traditional notebooks. Scale-up model development with simple connectivity to Vertex AI services. Simplified access to data and in-notebook access to machine learning with BigQuery, Dataproc, Spark, and Vertex AI integration. Take advantage of the power of infinite computing with Vertex AI training for experimentation and prototyping, to go from data to training at scale. Using Vertex AI Workbench you can implement your training, and deployment workflows on Vertex AI from one place. A Jupyter-based fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities. Explore data and train ML models with easy connections to Google Cloud's big data solutions.Starting Price: $10 per GB
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40
ELCA Smart Data Lake Builder
ELCA Group
Classical Data Lakes are often reduced to basic but cheap raw data storage, neglecting significant aspects like transformation, data quality and security. These topics are left to data scientists, who end up spending up to 80% of their time acquiring, understanding and cleaning data before they can start using their core competencies. In addition, classical Data Lakes are often implemented by separate departments using different standards and tools, which makes it harder to implement comprehensive analytical use cases. Smart Data Lakes solve these various issues by providing architectural and methodical guidelines, together with an efficient tool to build a strong high-quality data foundation. Smart Data Lakes are at the core of any modern analytics platform. Their structure easily integrates prevalent Data Science tools and open source technologies, as well as AI and ML. Their storage is cheap and scalable, supporting both unstructured data and complex data structures.Starting Price: Free -
41
BigLake
Google
BigLake is a storage engine that unifies data warehouses and lakes by enabling BigQuery and open-source frameworks like Spark to access data with fine-grained access control. BigLake provides accelerated query performance across multi-cloud storage and open formats such as Apache Iceberg. Store a single copy of data with uniform features across data warehouses & lakes. Fine-grained access control and multi-cloud governance over distributed data. Seamless integration with open-source analytics tools and open data formats. Unlock analytics on distributed data regardless of where and how it’s stored, while choosing the best analytics tools, open source or cloud-native over a single copy of data. Fine-grained access control across open source engines like Apache Spark, Presto, and Trino, and open formats such as Parquet. Performant queries over data lakes powered by BigQuery. Integrates with Dataplex to provide management at scale, including logical data organization.Starting Price: $5 per TB -
42
HStreamDB
EMQ
A streaming database is purpose-built to ingest, store, process, and analyze massive data streams. It is a modern data infrastructure that unifies messaging, stream processing, and storage to help get value out of your data in real-time. Ingest massive amounts of data continuously generated from various sources, such as IoT device sensors. Store millions of data streams reliably in a specially designed distributed streaming data storage cluster. Consume data streams in real-time as fast as from Kafka by subscribing to topics in HStreamDB. With the permanent data stream storage, you can playback and consume data streams anytime. Process data streams based on event-time with the same familiar SQL syntax you use to query data in a relational database. You can use SQL to filter, transform, aggregate, and even join multiple data streams.Starting Price: Free -
43
Apache PredictionIO
Apache
Apache PredictionIO® is an open-source machine learning server built on top of a state-of-the-art open-source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you quickly build and deploy an engine as a web service on production with customizable templates. Respond to dynamic queries in real-time once deployed as a web service, evaluate and tune multiple engine variants systematically, and unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics. Speed up machine learning modeling with systematic processes and pre-built evaluation measures, support machine learning and data processing libraries such as Spark MLLib and OpenNLP. Implement your own machine learning models and seamlessly incorporate them into your engine. Simplify data infrastructure management. Apache PredictionIO® can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Akka HTTP, etc.Starting Price: Free -
44
Akira AI
Akira AI
Akira AI gives best-in-class explainability, accuracy, scalability, stability, and speed in their application. Provide transparent, robust, trustworthy, and fair applications with responsible AI. Transforming the way enterprise work with end-to-end model deployment, computer vision techniques and machine learning solutions. Enable actionable insights to solve business-impacting ML model issues. Build compliant and responsible AI systems with proactive bias monitoring capabilities. Explainable ML and quality management solutions that open the AI black box to understand and optimize the correct inner workings of the model. Intelligent automation-enabled processes reduce operational hindrances and optimize workforce productivity. Build AI-quality solutions that optimize, explain, and monitor ML models. Improve performance, transparency, and robustness. Improve AI outcomes and drive model performance by increasing model velocity.Starting Price: $15 per month -
45
Kedro
Kedro
Kedro is the foundation for clean data science code. It borrows concepts from software engineering and applies them to machine-learning projects. A Kedro project provides scaffolding for complex data and machine-learning pipelines. You spend less time on tedious "plumbing" and focus instead on solving new problems. Kedro standardizes how data science code is created and ensures teams collaborate to solve problems easily. Make a seamless transition from development to production with exploratory code that you can transition to reproducible, maintainable, and modular experiments. A series of lightweight data connectors is used to save and load data across many different file formats and file systems.Starting Price: Free -
46
Tabular
Tabular
Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.Starting Price: $100 per month -
47
Apache Doris
The Apache Software Foundation
Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.Starting Price: Free -
48
Hue
Hue
Hue brings the best querying experience with the most intelligent autocomplete and query editor components. The tables and storage browsers leverage your existing data catalog knowledge transparently. Help users find the correct data among thousands of databases and self-document it. Assist users with their SQL queries and leverage rich previews for links, sharing from the editor directly in Slack. Several apps, each one specialized in a certain type of querying are available. Data sources can be explored first via the browsers. The editor shines for SQL queries. It comes with an intelligent autocomplete, risk alerts, and self-service troubleshooting. Dashboards focus on visualizing indexed data but can also query SQL databases. You can now search for certain cell values in the table and the results are highlighted. To make your SQL editing experience, Hue comes with one of the best SQL autocomplete on the planet.Starting Price: Free -
49
Yandex Data Proc
Yandex
You select the size of the cluster, node capacity, and a set of services, and Yandex Data Proc automatically creates and configures Spark and Hadoop clusters and other components. Collaborate by using Zeppelin notebooks and other web apps via a UI proxy. You get full control of your cluster with root permissions for each VM. Install your own applications and libraries on running clusters without having to restart them. Yandex Data Proc uses instance groups to automatically increase or decrease computing resources of compute subclusters based on CPU usage indicators. Data Proc allows you to create managed Hive clusters, which can reduce the probability of failures and losses caused by metadata unavailability. Save time on building ETL pipelines and pipelines for training and developing models, as well as describing other iterative tasks. The Data Proc operator is already built into Apache Airflow.Starting Price: $0.19 per hour -
50
Tonic Ephemeral
Tonic
Stop wasting time provisioning and maintaining databases yourself. Effortlessly create isolated test databases to ship features faster. Equip your developers with the ready-to-go data they need to keep fast-paced projects on track. Spin up pre-populated databases for testing purposes as part of your CI/CD pipeline, and automatically tear them down once the tests are done. Quickly and painlessly spin up databases at the click of a button for testing, bug reproduction, demos, and more with built-in container orchestration. Use our patented subsetter to shrink PBs down to GBs without breaking referential integrity, then leverage Tonic Ephemeral to spin up a database with only the data needed for development to cut cloud costs and maximize efficiency. Pair our patented subsetted with Tonic Ephemeral to get all the data subsets you need for only as long as you need them. Maximize efficiency by getting your developers access to one-off datasets for local development.Starting Price: $199 per month
