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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraphite  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.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called Whisper
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Websiteimpala.apache.orgwww.databricks.comwww.enterprisedb.comcloud.google.com/­bigtablegithub.com/­graphite-project/­graphite-web
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comwww.enterprisedb.com/­docscloud.google.com/­bigtable/­docsgraphite.readthedocs.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksEnterpriseDBGoogleChris Davis
Initial release20132013200520152006
Current release4.1.0, June 202214, December 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBSD for PostgreSQL-componentscommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CPython
Server operating systemsLinuxhostedLinux
Windows
hostedLinux
Unix
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoNumeric data only
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.nono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes infostandard with numerous extensionsnono
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)
HTTP API
Sockets
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
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.nono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangeShardingnone
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 zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
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)none
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes infolocking
Durability infoSupport for making data persistentyesyesyesyesyes
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)no
More information provided by the system vendor
Apache ImpalaDatabricksEDB PostgresGoogle Cloud BigtableGraphite
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache ImpalaDatabricksEDB PostgresGoogle Cloud BigtableGraphite
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