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DBMS > Apache Impala vs. Google Cloud Spanner vs. KeyDB vs. Microsoft Access

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. KeyDB vs. Microsoft Access

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­spannergithub.com/­Snapchat/­KeyDB
keydb.dev
www.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docsdocs.keydb.devdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleEQ Alpha Technology Ltd.Microsoft
Initial release2013201720191992
Current release4.1.0, June 20221902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSD-3commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemsLinuxhostedLinuxWindows infoNot a real database server, but making use of DLLs
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.nonono
Secondary indexesyesyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011noyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoLuayes infosince Access 2010 using the ACE-engine
Triggersnononoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationOptimistic locking, atomic execution of commands blocks and scriptsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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)simple password-based access control and ACLno infoa simple user-level security was built in till version Access 2003

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More resources
Apache ImpalaGoogle Cloud SpannerKeyDBMicrosoft Access
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