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DBMS > EJDB vs. Google Cloud Datastore vs. Graphite vs. InterSystems Caché vs. Microsoft Azure Synapse Analytics

System Properties Comparison EJDB vs. Google Cloud Datastore vs. Graphite vs. InterSystems Caché vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraphite  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperA multi-model DBMS and application serverElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument storeDocument storeTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­datastoregithub.com/­graphite-project/­graphite-webwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­synapse-analytics
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsgraphite.readthedocs.iodocs.intersystems.comdocs.microsoft.com/­azure/­synapse-analytics
DeveloperSoftmotionsGoogleChris DavisInterSystemsMicrosoft
Initial release20122008200619972016
Current release2018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCPythonC++
Server operating systemsserver-lesshostedLinux
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hosted
Data schemeschema-freeschema-freeyesdepending on used data modelyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes, details hereNumeric data onlyyesyes
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.nonoyesno
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesyes
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Sockets
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript (Node.js)
Python
C#
C++
Java
C#
Java
PHP
Server-side scripts infoStored proceduresnousing Google App EnginenoyesTransact SQL
TriggersnoCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenoneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosnoneSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.noneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes infolockingyesyes
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.noyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and rolesyes

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More resources
EJDBGoogle Cloud DatastoreGraphiteInterSystems CachéMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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