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DBMS > Bangdb vs. Ehcache vs. Google Cloud Datastore vs. TypeDB

System Properties Comparison Bangdb vs. Ehcache vs. Google Cloud Datastore vs. TypeDB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA widely adopted Java cache with tiered storage optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value storeDocument storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.70
Rank#230  Overall
#20  Graph DBMS
#106  Relational DBMS
Websitebangdb.comwww.ehcache.orgcloud.google.com/­datastoretypedb.com
Technical documentationdocs.bangdb.comwww.ehcache.org/­documentationcloud.google.com/­datastore/­docstypedb.com/­docs
DeveloperSachin Sinha, BangDBTerracotta Inc, owned by Software AGGoogleVaticle
Initial release2012200920082016
Current releaseBangDB 2.0, October 20213.10.0, March 20222.26.3, January 2024
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaJava
Server operating systemsLinuxAll OS with a Java VMhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes, 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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialnoyesyes
SQL infoSupport of SQLSQL like support with command line toolnoSQL-like query language (GQL)no
APIs and other access methodsProprietary protocol
RESTful HTTP API
JCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesC
C#
C++
Java
Python
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnonousing Google App Engineno
Triggersyes, Notifications (with Streaming only)yes infoCache Event ListenersCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infoby using Terracotta ServerShardingSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoby using Terracotta ServerMulti-source replication using PaxosMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyTunable Consistency (Strong, Eventual, Weak)Immediate 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesnono
User concepts infoAccess controlyes (enterprise version only)noAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infoat REST API level; other APIs in progress
More information provided by the system vendor
BangdbEhcacheGoogle Cloud DatastoreTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
BangdbEhcacheGoogle Cloud DatastoreTypeDB infoformerly named Grakn
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