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DBMS > Apache Druid vs. EJDB vs. Google Cloud Bigtable vs. Hazelcast

System Properties Comparison Apache Druid vs. EJDB vs. Google Cloud Bigtable vs. Hazelcast

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data grid
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value store
Wide column store
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score0.31
Rank#296  Overall
#44  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Websitedruid.apache.orggithub.com/­Softmotions/­ejdbcloud.google.com/­bigtablehazelcast.com
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docs
DeveloperApache Software Foundation and contributorsSoftmotionsGoogleHazelcast
Initial release2012201220152008
Current release29.0.1, April 20245.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGPLv2commercialOpen Source infoApache Version 2; 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 languageJavaCJava
Server operating systemsLinux
OS X
Unix
server-lesshostedAll OS with a Java VM
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idnoyes
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL for queryingnonoSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
in-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnononoyes infoEvent Listeners, Executor Services
Triggersnononoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operationsone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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.nonoyes
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)Role-based access control

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More resources
Apache DruidEJDBGoogle Cloud BigtableHazelcast
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