Top 10 Hive Alternatives & Competitors

The Relational Databases solutions below are the most common alternatives that users and reviewers compare with Hive. Other important factors to consider when researching alternatives to Hive include ease of use and reliability. The best overall Hive alternative is Microsoft SQL Server. Other similar apps like Hive are Postman, MySQL, Oracle Database, and Amazon Relational Database Service (RDS). Hive alternatives can be found in Relational Databases but may also be in iPaaS Software or API Platforms.

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Best Paid & Free Alternatives to Hive

Microsoft SQL Server
Postman
MySQL
Oracle Database
Amazon Relational Database Service (RDS)
MuleSoft Anypoint Platform
IBM Db2
PostgreSQL

Top 10 Alternatives to Hive Recently Reviewed By G2 Community

Browse options below. Based on reviewer data, you can see how Hive stacks up to the competition and find the best product for your business.

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By Microsoft

Product Description

SQL Server 2017 brings the power of SQL Server to Windows, Linux and Docker containers for the first time ever, enabling developers to build intelligent applications using their preferred language and environment. Experience industry-leading performance, rest assured with innovative security features, transform your business with AI built-in, and deliver insights wherever your users are with mobile BI.

Categories in common with Hive:

By Postman

Product Description

Categories in common with Hive:

By Oracle

Product Description

MySQL is the world's most popular open-source database, renowned for its reliability, performance, and ease of use. It serves as the backbone for many high-profile web applications, including those of Facebook, Twitter, and YouTube. MySQL offers a comprehensive suite of features that cater to the needs of modern web, mobile, embedded, and cloud applications. Key Features and Functionality: - Transactional Data Dictionary: Implemented as a set of SQL tables stored in a single InnoDB tablespace, enhancing data management efficiency. - Common Table Expressions (CTEs): Also known as WITH queries, CTEs simplify complex queries and improve readability. - Window Functions: These functions reduce code complexity and boost developer productivity by allowing calculations across sets of table rows related to the current row. - Invisible Indexes: Facilitate better management of software upgrades and database changes for applications that require continuous operation. - Descending Indexes: Eliminate the need for sorting results, leading to performance improvements. - JSON Support: Includes the JSON_TABLE() function, which accepts JSON data and returns it as a relational table, enhancing flexibility in data handling. - Document Store: Allows the development of both SQL and NoSQL document applications using a single database, providing versatility in application design. - SQL Roles: Simplify permission management by granting and denying permissions to groups of users, thereby reducing the security workload. - OpenSSL Integration: Utilizes OpenSSL as the default TLS/SSL library, ensuring secure data transmission. - Default to utf8mb4 Character Set: Supports richer mobile applications and international character sets, accommodating a global user base. - Geographic Information System (GIS) Enhancements: Supports geography and Spatial Reference Systems (SRS), enabling advanced spatial data analysis. - InnoDB Cluster: Provides improved high availability through integrated solutions. - InnoDB ClusterSet: Offers cross-region disaster recovery capabilities, ensuring data resilience. - Replication: Provides flexible topologies for scale-out and high availability, enhancing system robustness. - Reliability: Requires minimal intervention to achieve continuous uptime, ensuring consistent performance. - Partitioning: Improves performance and management of very large database environments by dividing tables into smaller, more manageable pieces. - ACID Transactions: Ensures reliable and secure business-critical applications by supporting Atomicity, Consistency, Isolation, and Durability. - Stored Procedures and Triggers: Enhance developer productivity and enforce complex business rules at the database level. - Views: Ensure sensitive information is not compromised by providing controlled access to data. - Ease of Use: Offers a "3 minutes from download to development" installation and configuration process, facilitating quick deployment. - Low Administration: Requires very little database maintenance, reducing operational overhead. Primary Value and User Solutions: MySQL delivers a robust, scalable, and secure database solution that addresses the needs of developers and enterprises alike. Its comprehensive feature set supports the development of high-performance applications across various platforms, including web, mobile, embedded, and cloud environments. By offering advanced functionalities such as ACID compliance, high availability, and flexible replication, MySQL ensures data integrity and reliability. Its ease of use and low administrative requirements enable organizations to reduce operational costs and accelerate time-to-market for their applications. Furthermore, MySQL's support for modern development practices, including JSON and NoSQL capabilities, allows developers to build versatile and future-proof applications.

Categories in common with Hive:

Relational Databases

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Amazon Relational Database Service (RDS)

By Amazon Web Services (AWS)

4.5/5

(901)

Product Description

Categories in common with Hive:

Relational Databases

MuleSoft Anypoint Platform

By Salesforce

4.5/5

(714)

Product Description

Categories in common with Hive:

By IBM

Product Description

Categories in common with Hive:

By PostgreSQL

Product Description

PostgreSQL is a powerful, open-source object-relational database system renowned for its reliability, extensibility, and adherence to SQL standards. Originating from the POSTGRES project at the University of California at Berkeley in 1986, it has evolved over nearly four decades into a robust platform capable of handling complex data workloads across various operating systems. PostgreSQL's architecture emphasizes data integrity and scalability, making it a preferred choice for developers and organizations worldwide. Key Features and Functionality: - Comprehensive Data Types: Supports a wide range of data types, including primitives (Integer, Numeric, String, Boolean), structured (Date/Time, Array, Range), document (JSON/JSONB, XML), and geometric types. - Advanced Data Integrity: Ensures data accuracy through features like UNIQUE constraints, primary and foreign keys, exclusion constraints, and various locking mechanisms. - High Performance and Concurrency: Utilizes advanced indexing methods (B-tree, GiST, GIN, BRIN), a sophisticated query planner, multi-version concurrency control (MVCC), parallel query execution, and table partitioning to optimize performance. - Reliability and Disaster Recovery: Offers write-ahead logging (WAL), various replication methods (asynchronous, synchronous, logical), point-in-time recovery (PITR), and active standbys to ensure data durability and availability. - Robust Security Measures: Provides multiple authentication methods (GSSAPI, SSPI, LDAP, SCRAM-SHA-256, Certificate, OAuth 2.0), a comprehensive access-control system, and supports multi-factor authentication. - Extensibility: Allows the creation of custom data types, functions, and operators. Supports procedural languages like PL/pgSQL, Perl, Python, and Tcl, with additional languages available through extensions. Primary Value and User Solutions: PostgreSQL addresses the needs of developers and organizations by offering a highly extensible and standards-compliant database system that ensures data integrity, scalability, and robust performance. Its open-source nature allows for continuous innovation and adaptability, enabling users to tailor the database to their specific requirements. Whether managing small applications or large-scale enterprise systems, PostgreSQL provides a reliable foundation for storing and processing data efficiently.

Categories in common with Hive:

Relational Databases