Top 10 Tiger Data Alternatives & Competitors

Top 10 Alternatives to Tiger Data Recently Reviewed By G2 Community

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Snowflake
By Snowflake, Inc.
4.6/5
(678)
Product Description
Snowflake’s platform eliminates data silos and simplifies architectures, so organizations can get more value from their data. The platform is designed as a single, unified product with automations that reduce complexity and help ensure everything “just works”. To support a wide range of workloads, it’s optimized for performance at scale no matter whether someone’s working with SQL, Python, or other languages. And it’s globally connected so organizations can securely access the most relevant content across clouds and regions, with one consistent experience.
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Reviewers say compared to Tiger Data, Snowflake is:
Easier to set up
More usable
Categories in common with Tiger Data:
Columnar Databases
Database Management Systems (DBMS)

InfluxDB
By InfluxData
4.4/5
(100)
Product Description
InfluxDB is the open source time series database
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Reviewers say compared to Tiger Data, InfluxDB is:
Easier to set up
Easier to admin
Categories in common with Tiger Data:
Real-time Analytic Database
Time Series Databases

Google Cloud SQL
By Google
4.5/5
(358)
Product Description
Cloud SQL is a fully managed, relational database service for running PostgreSQL, MySQL and SQL Server workloads. It's an ideal choice if you want to lift & shift an existing database or build a new application in the cloud.
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Reviewers say compared to Tiger Data, Google Cloud SQL is:
Easier to set up
Easier to admin
More usable
Categories in common with Tiger Data:
Database as a Service (DBaaS)
Database Management Systems (DBMS)
Relational Databases
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PostgreSQL
By PostgreSQL
4.4/5
(669)
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.
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Categories in common with Tiger Data:
Relational Databases

Microsoft SQL Server
By Microsoft
4.4/5
(2,261)
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.
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Reviewers say compared to Tiger Data, Microsoft SQL Server is:
More expensive
Categories in common with Tiger Data:
Database Management Systems (DBMS)
Relational Databases

Amazon Aurora
By Amazon Web Services (AWS)
4.5/5
(454)
Product Description
Amazon Aurora is a fully managed relational database service that combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. Compatible with MySQL and PostgreSQL, Aurora delivers up to five times the throughput of standard MySQL databases and up to three times that of standard PostgreSQL databases. It is designed for high availability, offering up to 99.99% availability within a single region and up to 99.999% across multiple regions. Aurora's architecture includes a distributed, fault-tolerant storage system that automatically scales up to 128 tebibytes, ensuring continuous data access and durability. Additionally, Aurora provides serverless configurations, allowing automatic scaling based on application needs, and integrates seamlessly with other AWS services for machine learning and analytics. Key Features and Functionality: - High Performance: Delivers up to five times the throughput of MySQL and three times that of PostgreSQL, enabling efficient handling of demanding workloads. - High Availability: Designed for up to 99.99% availability within a single region and up to 99.999% across multiple regions, ensuring continuous data access. - Scalability: Automatically scales storage up to 128 tebibytes and supports up to 15 read replicas for read-intensive applications. - Serverless Configuration: Offers Aurora Serverless, which automatically adjusts capacity based on application demand, eliminating the need for manual provisioning. - Machine Learning Integration: Integrates with Amazon SageMaker and Amazon Comprehend, allowing for in-database machine learning capabilities without data movement. - Security: Provides multiple layers of security, including network isolation, encryption at rest and in transit, and compliance with various industry standards. Primary Value and Solutions Provided: Amazon Aurora addresses the need for a high-performance, highly available, and scalable relational database service that is cost-effective and easy to manage. By offering compatibility with MySQL and PostgreSQL, it allows organizations to migrate existing applications without significant code changes. Aurora's automatic scaling and serverless options cater to applications with variable workloads, reducing operational overhead and costs. Its integration with AWS machine learning services enables real-time analytics and predictive capabilities directly within the database, enhancing application functionality. Overall, Aurora simplifies database management while delivering enterprise-grade performance and reliability.
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Reviewers say compared to Tiger Data, Amazon Aurora is:
More expensive
Easier to set up
Easier to admin
Categories in common with Tiger Data:
Database as a Service (DBaaS)
Relational Databases

MySQL
By Oracle
4.4/5
(1,669)
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.
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Reviewers say compared to Tiger Data, MySQL is:
Easier to set up
Categories in common with Tiger Data:
Relational Databases

ScyllaDB
By ScyllaDB
4.5/5
(364)
Product Description
Manage terabytes to petabytes of digital information with millions of read/write operations and msec P99 response. Our high availability architecture takes full advantage of modern infrastructure and networking capabilities. This translates to dramatically higher throughput and lower latency--eliminating barriers to scale.
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Categories in common with Tiger Data:
Database as a Service (DBaaS)

Amazon DynamoDB
By Amazon Web Services (AWS)
4.4/5
(525)
Product Description
Nonrelational database for applications that need performance at any scale
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Reviewers say compared to Tiger Data, Amazon DynamoDB is:
Easier to set up
Easier to admin
Categories in common with Tiger Data:
Database as a Service (DBaaS)

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