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DBMS > Apache Druid vs. CockroachDB vs. EJDB vs. Google Cloud Datastore

System Properties Comparison Apache Druid vs. CockroachDB vs. EJDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCockroachDB  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.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 Platform
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument storeDocument store
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
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Websitedruid.apache.orgwww.cockroachlabs.comgithub.com/­Softmotions/­ejdbcloud.google.com/­datastore
Technical documentationdruid.apache.org/­docs/­latest/­designwww.cockroachlabs.com/­docsgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation and contributorsCockroach LabsSoftmotionsGoogle
Initial release2012201520122008
Current release29.0.1, April 202424.1.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0, commercial license availableOpen Source infoGPLv2commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC
Server operating systemsLinux
OS X
Unix
Linux
macOS
Windows
server-lesshosted
Data schemeyes infoschema-less columns are supporteddynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, bool, date, object_idyes, details here
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
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingyes, wire compatible with PostgreSQLnoSQL-like query language (GQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBCin-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononousing Google App Engine
TriggersnononoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using RAFTnoneMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integritynoyesno infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoRead/Write Lockingyes
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.nonono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache DruidCockroachDBEJDBGoogle Cloud Datastore
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