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DBMS > EJDB vs. GigaSpaces vs. HarperDB vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

System Properties Comparison EJDB vs. GigaSpaces vs. HarperDB vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully managed big data interactive analytics platformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Document storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsGraph DBMS
Search engine
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
Score0.31
Rank#296  Overall
#44  Document stores
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.95
Rank#80  Overall
#42  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.gigaspaces.comwww.harperdb.ioazure.microsoft.com/­services/­data-explorerwww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.gigaspaces.com/­latest/­landing.htmldocs.harperdb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperSoftmotionsGigaspaces TechnologiesHarperDBMicrosoftSAP infoformerly Sybase
Initial release20122000201720191992
Current release15.5, September 20203.1, August 2021cloud service with continuous releases17, July 2015
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache Version 2; Commercial licenses availablecommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, C++, .NetNode.js
Server operating systemsserver-lessLinux
macOS
Solaris
Windows
Linux
OS X
hostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freedynamic schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyes infoJSON data typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.no infoXML can be used for describing objects metadatanoyesyes
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsSQL-like data manipulation statementsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsin-process shared libraryGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C++
Java
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyesCustom Functions infosince release 3.1Yes, possible languages: KQL, Python, Ryes, in C/C++, Java, .Net or Perl
Triggersnoyes, event driven architecturenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingA table resides as a whole on one (or more) nodes in a clusterSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infothe nodes on which a table resides can be definedyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlnoRole-based access controlAccess rights for users and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
EJDBGigaSpacesHarperDBMicrosoft Azure Data ExplorerSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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