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DBMS > BigchainDB vs. EsgynDB vs. Google Cloud Datastore vs. Teradata Aster vs. TimesTen

System Properties Comparison BigchainDB vs. EsgynDB vs. Google Cloud Datastore vs. Teradata Aster vs. TimesTen

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTimesTen  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPlatform for big data analytics on multistructured data sources and typesIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitewww.bigchaindb.comwww.esgyn.cncloud.google.com/­datastorewww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperEsgynGoogleTeradataOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20162015200820051998
Current release11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialcommercialcommercialcommercial
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 languagePythonC++, Java
Server operating systemsLinuxLinuxhostedLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or datenoyesyes, 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.nononoyes infoin Aster File Storeno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yesyes
APIs and other access methodsCLI Client
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresJava Stored Proceduresusing Google App EngineR packagesPL/SQL
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersMulti-source replication using Paxosyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BigchainDBEsgynDBGoogle Cloud DatastoreTeradata AsterTimesTen
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