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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTDengine  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.Microsoft 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.)Time Series DBMS and big data platform
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteimpala.apache.orgcloud.google.com/­spannerwww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docsdeveloper.microsoft.com/­en-us/­accessdocs.tdengine.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftTDEngine, previously Taos Data
Initial release2013201719922019
Current release4.1.0, June 20221902 (16.0.11328.20222), March 20193.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL V3, also commercial editions available
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 systemsLinuxhostedWindows infoNot a real database server, but making use of DLLsLinux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011yes infobut not compliant to any SQL standardStandard SQL with extensions for time-series applications
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
ADO.NET
DAO
ODBC
OLE DB
JDBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infosince Access 2010 using the ACE-engineno
Triggersnonoyes infosince Access 2010 using the ACE-engineyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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)no infoa simple user-level security was built in till version Access 2003yes
More information provided by the system vendor
Apache ImpalaGoogle Cloud SpannerMicrosoft AccessTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache ImpalaGoogle Cloud SpannerMicrosoft AccessTDengine
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