Data Lakehouse Software – What to Know [3+ Top Picks]

Data lakehouses are open data management architectures that combine elements of data warehouses with aspects of data lakes.

Basically, a data lakehouse combines the flexibility and cost-efficiency of data lakes with the ACID transaction capabilities of data warehouses.

The new architecture started to gain steam when it was first introduced at the start of the 2020s.

However, the product category is starting to really take off now that large tech companies such as Microsoft, Oracle, Amazon are unveiling plans to implement this architecture in their systems.

What’s next for data lakehouses

Data lakehouses are part of the Next-gen Data Management trend.

Many current data management solutions are either costly, inflexible, or lack reliable security (or all of the above).

Furthermore, traditional, on-premise data warehouses are often not very scalable.

This has created a need for modernized data management architectures.

Next-gen data management architectures are natively compatible with cloud computing, which makes them able to handle massive volumes of data.

The rise of next-gen data management architectures will play a big role in the growth of the entire enterprise data management market (which is expected to double in the next five years).

What is lakehouse data?

Lakehouse data is a new type of data that is becoming increasingly popular.

It is a combination of data from both Data Lakes and Data Warehouses.

Lakehouse data is often seen as more reliable and trustworthy than Data Lake data because it has been through the ACID transaction process of Data Warehouses.

Furthermore, Data Lakehouses are often seen as more scalable than Data Warehouses.

Because of these reasons, Data Lakehouses are becoming more popular for storing large amounts of data.

(Source: Oracle)

Building the data lakehouse

The Data Lakehouse is a new type of data management architecture that combines the best aspects of Data Lakes and Data Warehouses.

When building a Data Lakehouse, it is important to consider the following:

• The type of data you want to store (structured, unstructured, or both)
• The volume of data you want to store
• The speed at which you want to be able to access the data
• The level of security you need
• The cost of storage and computing power

Data Lakehouses are becoming increasingly popular due to their ability to store large amounts of data at a lower cost than Data Warehouses.

Furthermore, Data Lakehouses offer more flexibility and scalability than Data Warehouses.

Data lakehouse architecture

Data lakehouses are open data management architectures that combine the best aspects of data warehouses and data lakes.

Data lakehouses are built on a shared-nothing architecture, which means that each node in the system is independent and can scale horizontally.

They also have a columnar storage format, which makes them more efficient than traditional row-based data warehouses.

Data lakehouses can be deployed on-premise or in the cloud.

The benefits of data lakehouses

Data lakehouses offer many benefits over traditional data management architectures.

Data lakehouses are more scalable than data warehouses, they are more flexible, and they offer better performance.

Data lakehouses also have a lower total cost of ownership than data warehouses.

Lakehouse vs. Data lake

It is important to note that Data Lakehouses are not the same as Data Lakes.

Data Lakes are a type of data repository that is used to store large amounts of unstructured data.

Data lakes are often used for data mining and analytics.

Data Lakehouses, on the other hand, are designed to store both structured and unstructured data.

They are also designed to be more scalable and efficient than Data Lakes.

What’s next for data lakehouses?

The future of data lakehouses is looking bright.

As more and more organizations adopt this new type of data management architecture, we can expect to see even more innovation in the space.

We can also expect to see Data Lakehouses becoming more popular for storing large amounts of data.

Best Data Lakehouses

#1 Azure Data Lakehouse

Azure Data Lakehouse is a cloud-based data management architecture that combines the best aspects of Data Lakes and Data Warehouses.

Azure Data Lakehouse is designed to be scalable, efficient, and secure.

It offers many benefits over traditional data architectures, including better performance, lower costs, and more flexibility.

If you are looking for a Data Lakehouse solution, Azure Data Lakehouse is a great option.

#2 Amazon Redshift Spectrum

Amazon Redshift Spectrum is a similar cloud-based data management architecture.

#3 Oracle

Oracle is also getting into this emerging industry.

They offer a cloud-based Data Lakehouse solution called Oracle Big Data Service.

This service is designed to be scalable, efficient, and secure.

If you are considering a Data Lakehouse solution, Oracle Big Data Service is worth considering.

Final thoughts – Data Lakehouse

Data Lakehouses are a new type of data management architecture that combines the best aspects of Data Lakes and Data Warehouses.

Data Lakehouses offer many benefits over traditional data architectures, including better performance, lower costs, and more flexibility.

Data lakehouses are more scalable than data warehouses, they are more flexible, and they offer better performance.

Data lakehouses also have a lower total cost of ownership than data warehouses.

If you are looking for a Data Lakehouse solution, Azure Data Lakehouse, Amazon Redshift Spectrum, and Oracle Big Data Service are all great options.

If you are considering building a Data Lakehouse, it is important to consider the type of data you want to store, the volume of data you want to store, the speed at which you want to be able to access the data, and the level of security you need.

The future of data lakehouses is looking bright. As more and more organizations adopt this new type of data management architecture, we can expect to see even more innovation in the space. We can also expect to see Data Lakehouses becoming more popular for storing large amounts of data.