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DBMS > Apache Druid vs. BigObject vs. Google Cloud Datastore vs. YottaDB

System Properties Comparison Apache Druid vs. BigObject vs. Google Cloud Datastore vs. YottaDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for real-time computations and queriesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast and solid embedded Key-value store
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infoa hierachical model (tree) can be imposedDocument storeKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.28
Rank#306  Overall
#44  Key-value stores
Websitedruid.apache.orgbigobject.iocloud.google.com/­datastoreyottadb.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.bigobject.iocloud.google.com/­datastore/­docsyottadb.com/­resources/­documentation
DeveloperApache Software Foundation and contributorsBigObject, Inc.GoogleYottaDB, LLC
Initial release2012201520082001
Current release29.0.1, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercialOpen Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC
Server operating systemsLinux
OS X
Unix
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedDocker
Linux
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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 indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query language (GQL)by using the Octo plugin
APIs and other access methodsJDBC
RESTful HTTP/JSON API
fluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
PostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresnoLuausing Google App Engine
TriggersnonoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate 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.
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users and groups based on OS-security mechanisms

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More resources
Apache DruidBigObjectGoogle Cloud DatastoreYottaDB
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