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DBMS > Databend vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. ToroDB

System Properties Comparison Databend vs. Google Cloud Datastore vs. LevelDB vs. Microsoft Access vs. ToroDB

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft 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.)A MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#300  Overall
#136  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score2.75
Rank#107  Overall
#19  Key-value stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastoregithub.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­torodb/­server
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­access
DeveloperDatabend LabsGoogleGoogleMicrosoft8Kdata
Initial release20212008201119922016
Current release1.0.59, April 20231.23, February 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++C++Java
Server operating systemshosted
Linux
macOS
hostedIllumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsAll OS with a Java 7 VM
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details herenoyesyes infostring, integer, double, boolean, date, object_id
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 indexesnoyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noyes infobut not compliant to any SQL standard
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnousing Google App Enginenoyes infosince Access 2010 using the ACE-engine
TriggersnoCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosnonenoneSource-replica replication
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes 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.no
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono infoa simple user-level security was built in till version Access 2003Access rights for users and roles

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More resources
DatabendGoogle Cloud DatastoreLevelDBMicrosoft AccessToroDB
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