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DBMS > Badger vs. EJDB vs. Google Cloud Datastore vs. IBM Db2 warehouse vs. Teradata

System Properties Comparison Badger vs. EJDB vs. Google Cloud Datastore vs. IBM Db2 warehouse vs. Teradata

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Embeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud-based data warehousing serviceA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value storeDocument storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.27
Rank#297  Overall
#44  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdbcloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehousewww.teradata.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgergithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsdocs.teradata.com
DeveloperDGraph LabsSoftmotionsGoogleIBMTeradata
Initial release20172012200820141984
Current releaseTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPLv2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC
Server operating systemsBSD
Linux
OS X
Solaris
Windows
server-lesshostedhostedhosted
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes infostring, integer, double, bool, date, object_idyes, 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.nonono infoImport/export of XML data possibleyes
Secondary indexesnonoyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSQL-like query language (GQL)yesyes infoSQL 2016 + extensions
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGoActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonousing Google App EnginePL/SQL, SQL PLyes infoUDFs, stored procedures, table functions in parallel
TriggersnonoCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication using PaxosyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
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.nonoyesyes
User concepts infoAccess controlnonoAccess 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
BadgerEJDBGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBTeradata
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