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DBMS > BigchainDB vs. Google Cloud Datastore vs. Ignite vs. TimesTen vs. WakandaDB

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. Ignite vs. TimesTen vs. WakandaDB

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  Xexclude from comparisonTimesTen  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.In-Memory RDBMS compatible to OracleWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeDocument storeKey-value store
Relational DBMS
Relational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.85
Rank#208  Overall
#35  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.bigchaindb.comcloud.google.com/­datastoreignite.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.htmlwakanda.github.io
Technical documentationbigchaindb.readthedocs.io/­en/­latestcloud.google.com/­datastore/­docsapacheignite.readme.io/­docsdocs.oracle.com/­database/­timesten-18.1wakanda.github.io/­doc
DeveloperGoogleApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Wakanda SAS
Initial release20162008201519982012
Current releaseApache Ignite 2.611 Release 2 (11.2.2.8.0)2.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoAGPL v3commercialOpen Source infoApache 2.0commercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languagePythonC++, Java, .NetC++, JavaScript
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyesyes
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.nonoyesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsCLI Client
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)PL/SQLyes
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosyes (replicated cache)Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
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.Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsfine grained access rights according to SQL-standardyes

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More resources
BigchainDBGoogle Cloud DatastoreIgniteTimesTenWakandaDB
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