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DBMS > EJDB vs. GigaSpaces vs. Hypertable vs. Microsoft Azure Data Explorer vs. Teradata

System Properties Comparison EJDB vs. GigaSpaces vs. Hypertable vs. Microsoft Azure Data Explorer vs. Teradata

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 TransactionsAn open source BigTable implementation based on distributed file systems such as HadoopFully managed big data interactive analytics platformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Wide column 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.gigaspaces.comazure.microsoft.com/­services/­data-explorerwww.teradata.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.teradata.com
DeveloperSoftmotionsGigaspaces TechnologiesHypertable Inc.MicrosoftTeradata
Initial release20122000200920191984
Current release15.5, September 20200.9.8.11, March 2016cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache Version 2; Commercial licenses availableOpen Source infoGNU version 3. Commercial license 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++, .NetC++
Server operating systemsserver-lessLinux
macOS
Solaris
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
hostedhosted
Linux
Data schemeschema-freeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesnoyes 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 metadatayesyes
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansall fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoKusto Query Language (KQL), SQL subsetyes infoSQL 2016 + extensions
APIs and other access methodsin-process shared libraryGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
C++ API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C++
Java
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, Ryes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes, event driven architecturenoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
selectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesSpark 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 datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoRole-based access controlnoAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
EJDBGigaSpacesHypertableMicrosoft Azure Data ExplorerTeradata
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