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DBMS > Apache Impala vs. Databricks vs. EDB Postgres vs. Google Cloud Bigtable

System Properties Comparison Apache Impala vs. Databricks vs. EDB Postgres vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websiteimpala.apache.orgwww.databricks.comwww.enterprisedb.comcloud.google.com/­bigtable
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.enterprisedb.com/­docscloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksEnterpriseDBGoogle
Initial release2013201320052015
Current release4.1.0, June 202214, December 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBSD for PostgreSQL-componentscommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemsLinuxhostedLinux
Windows
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes infostandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Apache ImpalaDatabricksEDB PostgresGoogle Cloud Bigtable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksEDB PostgresGoogle Cloud Bigtable
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