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DBMS > GridDB vs. LevelDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. SAP Advantage Database Server

System Properties Comparison GridDB vs. LevelDB vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. SAP Advantage Database Server

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonSAP Advantage Database Server infoformer name: Sybase ADS  Xexclude from comparison
SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsLow-cost RDBMS with access to ISAM and FoxPro data structures
Primary database modelTime Series DBMSKey-value storeRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitegriddb.netgithub.com/­google/­leveldbazure.microsoft.com/­services/­data-explorerwww.sadasengine.comwww.sap.com/products/advantage-database-server.html
Technical documentationdocs.griddb.netgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperToshiba CorporationGoogleMicrosoftSADAS s.r.l.Sybase, SAP
Initial release20132011201920061993
Current release5.1, August 20221.23, February 2021cloud service with continuous releases8.0
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSDcommercialcommercial infofree trial version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++
Server operating systemsLinuxIllumos
Linux
OS X
Windows
hostedAIX
Linux
Windows
Linux
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesnono
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noKusto Query Language (KQL), SQL subsetyesyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
.NET Client API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Delphi
Perl
PHP
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnoyes
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoCONFLICT Trigger to resolve replication conflicts
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'no infocaching of (temporary) tables can be configured
User concepts infoAccess controlAccess rights for users can be defined per databasenoAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBLevelDBMicrosoft Azure Data ExplorerSadas EngineSAP Advantage Database Server infoformer name: Sybase ADS
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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GridDBLevelDBMicrosoft Azure Data ExplorerSadas EngineSAP Advantage Database Server infoformer name: Sybase ADS
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