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DBMS > BigObject vs. EsgynDB vs. Google Cloud Datastore vs. Hive vs. Sadas Engine

System Properties Comparison BigObject vs. EsgynDB vs. Google Cloud Datastore vs. Hive vs. Sadas Engine

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websitebigobject.iowww.esgyn.cncloud.google.com/­datastorehive.apache.orgwww.sadasengine.com
Technical documentationdocs.bigobject.iocloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperBigObject, Inc.EsgynGoogleApache Software Foundation infoinitially developed by FacebookSADAS s.r.l.
Initial release20152015200820122006
Current release3.1.3, April 20228.0
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialOpen Source infoApache Version 2commercial infofree trial version available
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++, JavaJavaC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedAll OS with a Java VMAIX
Linux
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (GQL)SQL-like DML and DDL statementsyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
JDBC
ODBC
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresLuaJava Stored Proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceno
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersMulti-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
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.yesnonoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
BigObjectEsgynDBGoogle Cloud DatastoreHiveSadas Engine
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