HBase vs Impala: Compare Which is Better for 2019
In our last HBase tutorial, we discussed HBase vs RDBMS. Today, we will see HBase vs Impala. There is always a question occurs that while we have HBase then why to choose Impala over HBase instead of simply using HBase.
So to clear this doubt, here is an article “HBase vs Impala: Feature-wise Comparison”. First, we will see the meaning of HBase & Impala. Also, we will see the uses of Impala and HBase.
So, let’s start the difference between HBase vs Impala.
Difference Between HBase and Impala
Before we start discussing Difference between HBase and Impala, let’s see what are these two terms?
- What is HBase?
A very popular non-relational database on Hadoop which stores data in a column-oriented store model is HBase. In HBase, HDFS is used as data storage layer and to process data it uses MapReduce. Basically, HBase is a complete nonrelational database running on Hadoop.
Moreover, HBase uses SQL statements to submit queries while processing the data in tables on HDFS and also supports the concepts of databases, tables, and columns.
- What is Impala?
Apache Impala offers great flexibility to query data in HBase tables. Moreover, for bulk loads and full-table-scan queries, Impala tables process data files stored on HDF great; although, by performing individual row or range lookups, HBase can perform efficient data processing.
More specifically, Impala considers HBase a key-value store where a key is mapped to one column in the Impala table whereas value fields are mapped to other columns.
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Confused between HBase and Impala?
If our data is already stored in HBase but we want to use SQL requests since it is not possible as such with HBase, or even if we desire to join data from an HBase table with data from a MySQL table its one solution is, we can use Impala over HBase.
HBase vs Impala: Feature-wise Comparison
Below we are discussing the feature wise difference of HBase vs Impala:
i. Primary Database Model
Primary database model of HBase is Wide column store. Basically, with the ability to hold very large numbers of dynamic columns, Wide column stores store data in records. It is also known as extensible record stores
Whereas, primary database model of Impala is Relational DBMS. Basically, RDBMS support the relational data model and by the table name and a fixed number of attributes with fixed data types, its schema is defined.
Originally HBase was developed by Powerset, but now it is Apache’s top-level project.
Whereas, Impala is developed by Cloudera.
iii. Initial Release
Initially, it was released in the year 2008.
In the year 2013, Impala was released.
iv. Current Release
The current release of HBase is 1.4.3, in the year 2018, April.
And, the current release of Apache Impala is 2.10.0.
v. License Info
Under Apache version 2, HBase is Open Source.
Similarly, Apache Impala is also open source, under Apache version 2.
vi. Implementation Language
The implementation language of HBase is Java.
Whereas, implementation language of Impala is C++.
vii. Server Operating Systems
There are some server operating systems of HBase are Linux, Unix, Windows
And, for Impala, Linux is one server operating system only.
viii. Support of SQL
There is no support of SQL in HBase.
But, in Impala, SQL supports.
ix. APIs and Other Access Methods
HBase offers several APIs, such as Java API, RESTful HTTP API, and Thrift.
Whereas, Impala offers APIs as JDBC and ODBC.
x. Supported Programming Languages
HBase supports various languages such as C, C#, C++, Groovy, Java, PHP, Python, and Scala.
And, Impala supports all languages supporting JDBC/ODBC.
xi. Partitioning Methods
Apache HBase supports Sharding method for storing different data on different nodes.
Similarly, Impala also supports Sharding method for storing different data on different nodes.
xii. Consistency Concepts
HBase supports Immediate Consistency.
It supports Eventual Consistency.
Uses – HBase vs Impala
- Use of HBase
- In order to have random, real-time read/write access to Big Data, we prefer Apache HBase.
- We can easily host very large tables on top of clusters of commodity hardware with the help of HBase.
- Next, to Google’s Bigtable, HBase is a non-relational database model. To understand more, Bigtable acts up on Google File System, similarly, HBase works on top of Hadoop and HDFS.
- Use of Impala
- In simple words, to play well with BI tools Impala is designed.
- Also, it offers Standard ANSI SQL (92, with 2003 analytic extensions), UDFs/UDAs, correlated subqueries, nested types, and many more.
- There are various Data types Impala supports, such as Integer and floating point types, STRING, CHAR, VARCHAR, TIMESTAMP.
So, this was all about HBase vs Impala. Hope you like our explanation.
Hence, in this HBase vs Impala tutorial, we have seen the complete feature-wise Comparison on HBase vs Impala. However, to learn deeply about them, you can also refer relevant links given in blog to understand well. Still, if any doubt, ask in the comment tab.