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DBMS > etcd vs. Google Cloud Datastore vs. Informix vs. Microsoft Access

System Properties Comparison etcd vs. Google Cloud Datastore vs. Informix vs. Microsoft Access

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataMicrosoft 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 modelKey-value storeDocument storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorewww.ibm.com/­products/­informixwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
developer.microsoft.com/­en-us/­access
DeveloperGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Microsoft
Initial release200819841992
Current release3.4, August 201914.10.FC5, November 20201902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availablecommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++ and JavaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Windows infoNot a real database server, but making use of DLLs
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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.nono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesyes infobut not compliant to any SQL standard
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnousing Google App Engineyesyes infosince Access 2010 using the ACE-engine
Triggersyes, watching key changesCallbacks using the Google Apps Engineyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using PaxosMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authentication, authorization, and auditing controlsno infoa simple user-level security was built in till version Access 2003

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More resources
etcdGoogle Cloud DatastoreInformixMicrosoft Access
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