With the advancement in technology, the competition among the companies offering similar products is increasing day by day. This competition is relatively high among the companies providing technologies related to data. When it comes to Database Management, the choice between Greenplum and Snowflake is quite tricky.
Greenplum Database is a Massively Parallel Processing (MPP) SQL database built and based on PostgreSQL. It can expand to a multi-petabyte data burden without a hitch. It provides access to a cluster of powerful servers that will collaborate within a single SQL interface where you can examine all your data. Snowflake is a data warehouse company that provides uniform access and storage across cloud platforms. It strengthens its position as a service that requires practically little maintenance to provide secure access to your data.
In this blog, you will be exploring Greenplum vs Snowflake by understanding the 5 critical differences. It also explains the fundamentals of Greenplum and Snowflake before digging into the differences.
Table of Content
Introduction to Greenplum
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Greenplum Database is a Massively Parallel Processing (MPP) database server with a mainly built architecture for managing large-scale analytic Data Warehousing and Business Intelligence workloads.
Greenplum, which is based on the PostgreSQL 8.3.23 architecture, essentially uses several PostgreSQL database instances simultaneously in a single Greenplum cluster. PostgreSQL users will quickly become acquainted with Greenplum since many features, settings, and capabilities are the same and contain features designed to maximize how PostgreSQL works for business intelligence (BI) jobs and workloads.
Greenplum also provided advanced capabilities that PostgreSQL does not have, such as parallel data loading, resource management, storage upgrades, and sophisticated query optimization.
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Greenplum provides the following major features:
- Cloud-Independent for Flexible Deployment: Greenplum is accessible with “bring your own license” and hourly consumption models on popular public cloud markets, including Amazon Web Services, Microsoft Azure, and Google Cloud Platform. It is also available for private clouds powered by VMware vSphere and OpenStack. Best of all, all clouds use the same Greenplum version and tools for a consistent experience.
- Handle Streaming Data and Cloud Data with Ease: Greenplum provides Confluent-certified interaction with the Kafka ecosystem. Greenplum enables quick event processing for streaming use scenarios in conjunction with increased low-latency writes. The ability to query Amazon S3 items on-site leads to greater cloud data integration.
- Analytics from Business Intelligence to Artificial Intelligence: Analytics ranging from business intelligence to artificial intelligence is available in a single scale-out MPP database, which includes Machine Learning, Deep Learning, graph, text, and statistical methodologies. Support for R and Python analytical libraries, as well as Keras and Tensorflow, is extensive.
- Maximize Uptime and Protect Data Integrity: Greenplum has capabilities for high availability, intelligent fault detection, and rapid online differential recovery, as well as full and incremental backup and disaster recovery. Enterprise policy and regulatory needs are addressed through security and authentication capabilities.
Some of Greenplum’s important use cases are as follows:
- Machine Learning: Greenplum is an effective database for Machine Learning, which is the study of computer systems that improve themselves automatically over time. Apache MADlib is an open-source, SQL-based machine learning library that works in Greenplum and PostgreSQL databases. This combination improves your Greenplum Machine Learning deployment’s parallelism, scalability, and prediction accuracy. MADlib also provides data transformation and feature engineering tools for Machine Learning, such as descriptive and inferential statistics, pivoting, sessionization, and categorical encoding variables.
- Artificial Intelligence: Greenplum is an excellent database for applications that want to emulate human talents using intelligent computers. Greenplum’s capacity to ingest enormous amounts of data at quick rates makes it a valuable tool for intelligent applications that require intelligent interaction based on an infinite number of distinct circumstances.
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Introduction to Snowflake
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Snowflake is a cloud-based Data Warehousing technology that provides businesses with a scalable and flexible storage system. It is excellent for storing data that can subsequently be searched and retrieved by a business intelligence system. Even though it is entirely created and hosted in the cloud, it works well with cloud and on-premise BI systems.
Storage and Computational resources can be acquired individually using a subscription-based strategy. It also provides elastic storage, which uses both hot and cold storage strategies to save expenses and scalable computation, avoiding the usual concurrency limits of other Data Warehousing systems.
Snowflake’s unique architecture blends compute and storage natively. This architecture enables your users and data workloads to virtually access a single copy of your data while maintaining performance. Snowflake will allow you to execute your data solution across many locations and clouds to provide a consistent experience. Snowflake makes it feasible by abstracting the underlying complexities of Cloud infrastructures.
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Snowflake provides the following major features:
- Better Decision Making: Snowflake enables you to eliminate data silos and offer access to relevant insights throughout your business. This is a necessary first step in improving partner relationships, optimizing pricing, lowering operational expenses, increasing sales effectiveness, etc.
- Improved User Experience: With Snowflake, you may better understand user behavior and product usage. You may also use data to provide customer success, increase product offerings, and stimulate data science innovation.
- Robust Security: You may use a secure data lake as a central repository for all compliance and cybersecurity data. Snowflake Data Lakes provide rapid incident response. This lets you see the whole picture of an occurrence by aggregating large amounts of log data in a single location and evaluating years of log data in seconds. Semi-structured logs and structured corporate data may now be combined in a single data lake. Snowflake allows you to get your foot in the door without indexing and alter and change data once it’s there.
- Better Analytics: By transitioning from nightly batch loads to real-time data streams, Snowflake enables you to enhance your analytics pipeline. You may improve the quality of analytics in your business by allowing secure, concurrent, and controlled access to your Data Warehouse throughout the enterprise. This enables firms to optimize resource allocation to maximize revenue while reducing expenses and human work.
Some of Snowflake’s important use cases are as follows:
- Reporting: Data Warehouses allow your team to execute more business reporting on a grander scale, faster. Moving data to the cloud makes it simpler to rearrange information to be more valuable and understandable to business users.
- Analytics: Snowflake allows you to execute data analysis at any scale to gain the insights you want. Incorporating it into your larger systems will bring value to operational business applications.
Major Differences Between Greenplum and Snowflake
Now that you have a solid knowledge of Greenplum and Snowflake let us look at the essential characteristics that differentiate these ideas. Consider the following 5 elements that separate Greenplum from Snowflake:
1. Greenplum vs Snowflake: Functionality
Greenplum is an open-source database based on PostgreSQL for managing large-scale analytic Data Warehousing and Business Intelligence workloads. Snowflake is a commercially licensed cloud-based Data Warehouse solution that works with semi-structured and structured data. However, Greenplum and Snowflake are both ACID compliant. Snowflake has an advantage over Greenplum due to its ability to divide computing and storage via virtual data warehouses.
2. Greenplum vs Snowflake: Pricing
Greenplum is an open-source database, and the community version may be downloaded and used for free. In contrast, Snowflake pricing is based on the volume of data stored and the compute time you use. You can try Snowflake on 30-day free trial and later can choose the plans as per your business requirements as shown below:
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- Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making.
- Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
- Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
- Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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3. Greenplum vs Snowflake: Security
Greenplum provides high availability, intelligent fault detection, quick online differential recovery, and complete and incremental backup and disaster recovery. Enterprise policy and regulatory needs are addressed through security and authentication capabilities. In contrast, all imported data saved in Snowflake tables is AES-256 strong encrypted. All files kept in internal stages for data loading and unloading are automatically protected with robust AES-256 encryption.
4. Greenplum vs Snowflake: Support
In terms of support, both Greenplum and Snowflake have a community available 24*7 to help their customers. Greenplum has the edge over Snowflake in terms of training as they provide free video tutorials for their users.
5. Greenplum vs Snowflake: Integrations Supported
Greenplum, an open-source database, offers integrations from 25 sources, including Apache Superset, DataGrip, Preset, etc. In contrast, Snowflake allows data integrations from 200+ sources, making it a better option.
Conclusion
This blog compares Greenplum and Snowflake in-depth, showing the 5 significant differences between the two, which are functionality, pricing, security, support, and integrations supported. It also goes through the fundamentals of these tools, such as their features and use cases, before delving into the distinctions. As a result, this blog aims to assist you in making an informed decision regarding Greenplum vs Snowflake based on your individual needs while keeping these five key differences in mind.
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In the comments box below, you may share your learning experience with Greenplum vs Snowflake.