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DBMS > Apache Impala vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. mSQL

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. mSQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Event Store optimized for Internet of Things use casesmSQL (Mini SQL) is a simple and lightweight RDBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Event Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.27
Rank#169  Overall
#76  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storehughestech.com.au/­products/­msql
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleIBMHughes Technologies
Initial release2013201520171994
Current release4.1.0, June 20222.04.4, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree developer edition availablecommercial infofree licenses can be provided
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++C
Server operating systemsLinuxhostedLinux infoLinux, macOS, Windows for the developer additionAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infothrough the embedded Spark runtimeA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggers
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Delphi
Java
Perl
PHP
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistencynone
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableno
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
Apache ImpalaGoogle Cloud BigtableIBM Db2 Event StoremSQL infoMini SQL
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