Best Data Management Software for Streamkap
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Compare the Top Data Management Software that integrates with Streamkap as of July 2026
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This a list of Data Management software that integrates with Streamkap. Use the filters on the left to add additional filters for products that have integrations with Streamkap. View the products that work with Streamkap in the table below.
What is Data Management Software for Streamkap?
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security. Compare and read user reviews of the best Data Management software for Streamkap currently available using the table below. This list is updated regularly.
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1
Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.Starting Price: Free ($300 in free credits) -
2
Google Cloud SQL
Google
Fully managed relational database service for MySQL, PostgreSQL, and SQL Server with rich extension collections, configuration flags, and developer ecosystems. New customers get $300 in free credits to spend on Cloud SQL. You won’t be charged until you upgrade. Reduce maintenance costs with fully managed MySQL, PostgreSQL and SQL Server databases. Ensure business continuity with reliable and secure services backed by 24/7 SRE team. Data encryption at rest and in transit. Private connectivity with Virtual Private Cloud and user-controlled network access with firewall protection. Compliant with SSAE 16, ISO 27001, PCI DSS, and HIPAA. Scale your instances effortlessly with a single API call whether you start with simple testing or you need a highly available database in production. Simplify database operations with AI-powered assistance in Gemini, now in preview on Cloud SQL. It streamlines development, performance optimization, fleet management, governance, and migration.Starting Price: Free ($300 in free credits) -
3
MongoDB
MongoDB
MongoDB is a general purpose, document-based, distributed database built for modern application developers and for the cloud era. No database is more productive to use. Ship and iterate 3–5x faster with our flexible document data model and a unified query interface for any use case. Whether it’s your first customer or 20 million users around the world, meet your performance SLAs in any environment. Easily ensure high availability, protect data integrity, and meet the security and compliance standards for your mission-critical workloads. An integrated suite of cloud database services that allow you to address a wide variety of use cases, from transactional to analytical, from search to data visualizations. Launch secure mobile apps with native, edge-to-cloud sync and automatic conflict resolution. Run MongoDB anywhere, from your laptop to your data center.Starting Price: Free -
4
MySQL
Oracle
MySQL is the world's most popular open source database. With its proven performance, reliability, and ease-of-use, MySQL has become the leading database choice for web-based applications, used by high profile web properties including Facebook, Twitter, YouTube, and all five of the top five websites*. Additionally, it is an extremely popular choice as embedded database, distributed by thousands of ISVs and OEMs.Starting Price: Free -
5
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2/credit -
6
SQL Server
Microsoft
Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.Starting Price: Free -
7
Redis
Redis Labs
Redis Labs: home of Redis. Redis Enterprise is the best version of Redis. Go beyond cache; try Redis Enterprise free in the cloud using NoSQL & data caching with the world’s fastest in-memory database. Run Redis at scale, enterprise grade resiliency, massive scalability, ease of management, and operational simplicity. DevOps love Redis in the Cloud. Developers can access enhanced data structures, a variety of modules, and rapid innovation with faster time to market. CIOs love the confidence of working with 99.999% uptime best in class security and expert support from the creators of Redis. Implement relational databases, active-active, geo-distribution, built in conflict distribution for simple and complex data types, & reads/writes in multiple geo regions to the same data set. Redis Enterprise offers flexible deployment options, cloud on-prem, & hybrid. Redis Labs: home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.Starting Price: Free -
8
Amazon Aurora
Amazon
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups. Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones.Starting Price: $0.02 per month -
9
Elasticsearch
Elastic
Elastic is a search company. As the creators of the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash), Elastic builds self-managed and SaaS offerings that make data usable in real time and at scale for search, logging, security, and analytics use cases. Elastic's global community has more than 100,000 members across 45 countries. Since its initial release, Elastic's products have achieved more than 400 million cumulative downloads. Today thousands of organizations, including Cisco, eBay, Dell, Goldman Sachs, Groupon, HP, Microsoft, Netflix, The New York Times, Uber, Verizon, Yelp, and Wikipedia, use the Elastic Stack, and Elastic Cloud to power mission-critical systems that drive new revenue opportunities and massive cost savings. Elastic has headquarters in Amsterdam, The Netherlands, and Mountain View, California; and has over 1,000 employees in more than 35 countries around the world. -
10
Amazon DynamoDB
Amazon
Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multi-region, Multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and can support peaks of more than 20 million requests per second. Many of the world's fastest-growing businesses such as Lyft, Airbnb, and Redfin as well as enterprises such as Samsung, Toyota, and Capital One depend on the scale and performance of DynamoDB to support their mission-critical workloads. Focus on driving innovation with no operational overhead. Build out your game platform with player data, session history, and leaderboards for millions of concurrent users. Use design patterns for deploying shopping carts, workflow engines, inventory tracking, and customer profiles. DynamoDB supports high-traffic, extreme-scaled events. -
11
CockroachDB
Cockroach Labs
CockroachDB: Cloud-native, distributed SQL. Your cloud applications deserve a cloud-native database. Cloud-based apps and services deserve a database that scales across clouds, eases operational complexity, and improves reliability. CockroachDB delivers resilient, distributed SQL with ACID transactions and data partitioned by location. Automate operations for mission-critical applications by pairing CockroachDB with orchestration tools like Kubernetes and Mesosphere DC/OS. Every node can service both reads and writes so that you can scale query throughput and database capacity by simply adding more endpoints. Just add new nodes to CockroachDB, and it automatically rebalances data, completely removing the pain of manual sharding. As demand shifts, CockroachDB detects hotspots and intelligently distributes data to maintain performance. Tune your database at the row level so that data lives close to your users and you can minimize query latency. -
12
Apache Kafka
The Apache Software Foundation
Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages. -
13
ClickHouse
ClickHouse
ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. -
14
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 -
15
Amazon Redshift
Amazon
Amazon Redshift is a cloud-based data warehouse solution from AWS designed to deliver high-performance analytics and support modern AI-driven workloads. The platform enables organizations to analyze large volumes of structured and unstructured data across data warehouses, data lakes, and third-party sources using SQL. Redshift is built for scalability and cost efficiency, offering improved throughput and price-performance with AWS Graviton-powered RG instances and Redshift Serverless options. The solution also supports near real-time analytics through zero-ETL integrations that connect operational databases, streaming services, and enterprise applications without complex data pipelines. Amazon Redshift integrates with Amazon SageMaker and Amazon Bedrock to support advanced machine learning, analytics, and generative AI use cases.Starting Price: $0.543 per hour -
16
Azure Database for MySQL
Microsoft
Focus on application development with Azure Database for MySQL, which is cost-effective and easy to set up, operate, and scale. Enjoy advanced security, high availability, and a service-level agreement (SLA) of up to 99.99 percent. Fully managed MySQL, compatible with the latest community editions, provides maximum flexibility for database operations. Intelligent performance recommendations provide custom analysis and suggestions for MySQL database optimization. Simplified development experience and tight interoperability with Azure App Service and Azure Kubernetes Service (AKS). Enterprise-grade security and compliance, and enhanced security capabilities of Microsoft Defender for Identity. Easily build or migrate your workloads to Azure Database for MySQL. Set up, manage, and automate the maintenance of your MySQL database server, including routine updates, backups, and security. Build with the latest MySQL tools, drivers, and programming languages.Starting Price: $0.017 per hour -
17
IBM Db2
IBM
IBM Db2 is a family of data management products, including the Db2 relational database. The products feature AI-powered capabilities to help you modernize the management of both structured and unstructured data across on-premises and multicloud environments. By helping to make your data simple and accessible, the Db2 family positions your business to pursue the value of AI. Most of the Db2 family is available on the IBM Cloud Pak® for Data platform, either as an add-on or an included data source service, making virtually all of your data available across hybrid or multicloud environments to fuel your AI applications. Easily converge your transactional data stores and rapidly derive insights through universal, intelligent querying of data across disparate sources. Cut costs with the multimodel capability that eliminates the need for data replication and migration. Enhance agility by running Db2 on any cloud vendor. -
18
Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
19
PostgreSQL
PostgreSQL Global Development Group
PostgreSQL is a powerful, open-source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. There is a wealth of information to be found describing how to install and use PostgreSQL through the official documentation. The open-source community provides many helpful places to become familiar with PostgreSQL, discover how it works, and find career opportunities. Learm more on how to engage with the community. The PostgreSQL Global Development Group has released an update to all supported versions of PostgreSQL, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23. This release fixes 25 bugs reported over the last several months. This is the final release of PostgreSQL 10. PostgreSQL 10 will no longer receive security and bug fixes. If you are running PostgreSQL 10 in a production environment, we suggest that you make plans to upgrade. -
20
Azure Data Lake
Microsoft
Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. It removes the complexities of ingesting and storing all of your data while making it faster to get up and running with batch, streaming, and interactive analytics. Azure Data Lake works with existing IT investments for identity, management, and security for simplified data management and governance. It also integrates seamlessly with operational stores and data warehouses so you can extend current data applications. We’ve drawn on the experience of working with enterprise customers and running some of the largest scale processing and analytics in the world for Microsoft businesses like Office 365, Xbox Live, Azure, Windows, Bing, and Skype. Azure Data Lake solves many of the productivity and scalability challenges that prevent you from maximizing the -
21
Vitess
Vitess
A database clustering system for horizontal scaling of MySQL. Vitess combines many important MySQL features with the scalability of a NoSQL database. Its built-in sharding features let you grow your database without adding sharding logic to your application. Vitess automatically rewrites queries that hurt database performance. It also uses caching mechanisms to mediate queries and prevent duplicate queries from simultaneously reaching your database. Vitess automatically handles functions like master failovers and backups. It uses a lock server to track and administer servers, letting your application be blissfully ignorant of database topology. Vitess eliminates the high-memory overhead of MySQL connections. Vitess servers easily handle thousands of connections at once. MySQL doesn’t natively support sharding, but you will likely need it as your database grows. -
22
Apache Parquet
The Apache Software Foundation
We created Parquet to make the advantages of compressed, efficient columnar data representation available to any project in the Hadoop ecosystem. Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. We believe this approach is superior to simple flattening of nested namespaces. Parquet is built to support very efficient compression and encoding schemes. Multiple projects have demonstrated the performance impact of applying the right compression and encoding scheme to the data. Parquet allows compression schemes to be specified on a per-column level, and is future-proofed to allow adding more encodings as they are invented and implemented. Parquet is built to be used by anyone. The Hadoop ecosystem is rich with data processing frameworks, and we are not interested in playing favorites. -
23
DuckDB
DuckDB
Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access. -
24
MotherDuck
MotherDuck
We’re MotherDuck, a software company founded by a passionate flock of experienced data geeks. We’ve worked as leaders for some of the greatest companies in data. Scale-out is expensive and slow, let’s scale up. Big Data is dead, long live easy data. Your laptop is faster than your data warehouse. Why wait for the cloud? DuckDB slaps, so let’s supercharge it. When we founded MotherDuck we recognized that DuckDB might just be the next major game changer thanks to its ease of use, portability, lightning-fast performance, and rapid pace of community-driven innovation. At MotherDuck, we want to help the community, the DuckDB Foundation, and DuckDB Labs build greater awareness and adoption of DuckDB, whether users are working locally or want a serverless always-on way to execute their SQL. We are a world-class team of engineers and leaders with experience working on databases and cloud services at AWS, Databricks, Elastic, Facebook, Firebolt, Google BigQuery, Neo4j, SingleStore, and more. -
25
MariaDB
MariaDB
MariaDB Platform is a complete enterprise open source database solution. It has the versatility to support transactional, analytical and hybrid workloads as well as relational, JSON and hybrid data models. And it has the scalability to grow from standalone databases and data warehouses to fully distributed SQL for executing millions of transactions per second and performing interactive, ad hoc analytics on billions of rows. MariaDB can be deployed on prem on commodity hardware, is available on all major public clouds and through MariaDB SkySQL as a fully managed cloud database. To learn more, visit mariadb.com. -
26
Oracle Database
Oracle
Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. Oracle Autonomous Database, available on-premises via Oracle Cloud@Customer or in the Oracle Cloud Infrastructure, enables customers to simplify relational database environments and reduce management workloads. Oracle Autonomous Database eliminates the complexity of operating and securing Oracle Database while giving customers the highest levels of performance, scalability, and availability. Oracle Database can be deployed on-premises when customers have data residency and network latency concerns. Customers with applications that are dependent on specific Oracle database versions have complete control over the versions they run and when those versions change. -
27
Amazon DocumentDB
Amazon
Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs). -
28
Apache Flink
Apache Software Foundation
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.
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