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DBMS > Apache Druid vs. Hazelcast vs. jBASE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

System Properties Comparison Apache Druid vs. Hazelcast vs. jBASE vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHazelcast  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted in-memory data gridA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platformWidely used in-process key-value store
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeMultivalue DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitedruid.apache.orghazelcast.comwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdruid.apache.org/­docs/­latest/­designhazelcast.org/­imdg/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation and contributorsHazelcastRocket Software (formerly Zumasys)MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20122008199120191994
Current release29.0.1, April 20245.3.6, November 20235.7cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAIX
Linux
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesoptionalyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.noyes infothe object must implement a serialization strategyyesyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingSQL-like query languageEmbedded SQL for jBASE in BASICKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, Rno
Triggersnoyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoReplicated Mapyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlAccess rights can be defined down to the item levelAzure Active Directory Authenticationno

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More resources
Apache DruidHazelcastjBASEMicrosoft Azure Data ExplorerOracle Berkeley DB
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