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DBMS > BigObject vs. Blueflood vs. Datomic vs. Google Cloud Datastore vs. SAP SQL Anywhere

System Properties Comparison BigObject vs. Blueflood vs. Datomic vs. Google Cloud Datastore vs. SAP SQL Anywhere

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonBlueflood  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable TimeSeries DBMS based on CassandraDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.25
Rank#79  Overall
#43  Relational DBMS
Websitebigobject.ioblueflood.iowww.datomic.comcloud.google.com/­datastorewww.sap.com/­products/­technology-platform/­sql-anywhere.html
Technical documentationdocs.bigobject.iogithub.com/­rax-maas/­blueflood/­wikidocs.datomic.comcloud.google.com/­datastore/­docshelp.sap.com/­docs/­SAP_SQL_Anywhere
DeveloperBigObject, Inc.RackspaceCognitectGoogleSAP infoformerly Sybase
Initial release20152013201220081992
Current release1.0.6735, June 202317, July 2015
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache 2.0commercial infolimited edition freecommercialcommercial
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 languageJavaJava, Clojure
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
All OS with a Java VMhostedAIX
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyespredefined schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, details hereyes
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.nonononoyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like query language (GQL)yes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HTTP RESTRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
HTTP API
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresLuanoyes infoTransaction Functionsusing Google App Engineyes, in C/C++, Java, .Net or Perl
TriggersnonoBy using transaction functionsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on Cassandranone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on Cassandranone infoBut extensive use of caching in the application peersMulti-source replication using PaxosSource-replica replication infoDatabase mirroring
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate 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.Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BigObjectBluefloodDatomicGoogle Cloud DatastoreSAP SQL Anywhere infoformerly called Adaptive Server Anywhere
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