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DBMS > Apache Impala vs. etcd vs. Google Cloud Firestore vs. H2 vs. Microsoft Access

System Properties Comparison Apache Impala vs. etcd vs. Google Cloud Firestore vs. H2 vs. Microsoft Access

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed reliable key-value storeCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.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.)
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orgetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorewww.h2database.comwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationimpala.apache.org/­impala-docs.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestorewww.h2database.com/­html/­main.htmldeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleThomas MuellerMicrosoft
Initial release2013201720051992
Current release4.1.0, June 20223.4, August 20192.2.220, July 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoJavaC++
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLs
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyesyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
gRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, Firebase Rules & Cloud FunctionsJava Stored Procedures and User-Defined Functionsyes infosince Access 2010 using the ACE-engine
Triggersnoyes, watching key changesyes, with Cloud Functionsyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationWith clustering: 2 database servers on different computers operate on identical copies of a databasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes 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 KerberosnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003

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Apache ImpalaetcdGoogle Cloud FirestoreH2Microsoft Access
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