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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A widely adopted in-memory data grid
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Document storeKey-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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitedruid.apache.orgcloud.google.com/­bigtablewww.harperdb.iohazelcast.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docshazelcast.org/­imdg/­docs
DeveloperApache Software Foundation and contributorsGoogleHarperDBHazelcast
Initial release2012201520172008
Current release29.0.1, April 20243.1, August 20215.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJava
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
All OS with a Java VM
Data schemeyes infoschema-less columns are supportedschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyes
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.nononoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-like data manipulation statementsSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnonoCustom Functions infosince release 3.1yes infoEvent Listeners, Executor Services
Triggersnononoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
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 ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsAtomic execution of specific operationsone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesRole-based access control

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More resources
Apache DruidGoogle Cloud BigtableHarperDBHazelcast
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