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DBMS > Elasticsearch vs. HarperDB vs. Ignite vs. Microsoft Azure Data Explorer vs. ToroDB

System Properties Comparison Elasticsearch vs. HarperDB vs. Ignite vs. Microsoft Azure Data Explorer vs. ToroDB

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonHarperDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricUltra-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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelSearch engineDocument storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document 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
Score135.35
Rank#7  Overall
#1  Search engines
Score0.55
Rank#248  Overall
#38  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.elastic.co/­elasticsearchwww.harperdb.ioignite.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­torodb/­server
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.harperdb.io/­docsapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperElasticHarperDBApache Software FoundationMicrosoft8Kdata
Initial release20102017201520192016
Current release8.6, January 20233.1, August 2021Apache Ignite 2.6cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoElastic Licensecommercial infofree community edition availableOpen Source infoApache 2.0commercialOpen Source infoAGPL-V3
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 languageJavaNode.jsC++, Java, .NetJava
Server operating systemsAll OS with a Java VMLinux
OS X
Linux
OS X
Solaris
Windows
hostedAll OS with a Java 7 VM
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentdynamic schemayesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infostring, integer, double, boolean, date, object_id
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.nonoyesyesno
Secondary indexesyes infoAll search fields are automatically indexedyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subset
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
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
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1yes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, R
Triggersyes infoby using the 'percolation' featurenoyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infothe nodes on which a table resides can be definedyes (replicated cache)yes 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 methodsES-Hadoop Connectornoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.Memcached and Redis integrationyesyesno
User concepts infoAccess controlAccess rights for users and rolesSecurity Hooks for custom implementationsAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
ElasticsearchHarperDBIgniteMicrosoft Azure Data ExplorerToroDB
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