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DBMS > EJDB vs. HarperDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl

System Properties Comparison EJDB vs. HarperDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonHarperDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A widely adopted in-memory data gridFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeDocument storeKey-value storeRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
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
Score0.13
Rank#331  Overall
#46  Document stores
Score0.55
Rank#243  Overall
#38  Document stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.harperdb.iohazelcast.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.harperdb.io/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperSoftmotionsHarperDBHazelcastMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release20122017200820192012
Current release3.1, August 20215.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGPLv2commercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCNode.jsJavaJava
Server operating systemsserver-lessLinux
OS X
All OS with a Java VMhostedLinux
Data schemeschema-freedynamic schemaschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyes infoJSON data typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-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.noyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsin-process shared libraryJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersnonoyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infothe nodes on which a table resides can be definedyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsone or two-phase-commit; repeatable reads; read commitednoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoAccess rights for users and rolesRole-based access controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
EJDBHarperDBHazelcastMicrosoft Azure Data ExplorerSqrrl
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