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DBMS > Apache Phoenix vs. Heroic vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. SingleStore

System Properties Comparison Apache Phoenix vs. Heroic vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. SingleStore

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedDocument storeRelational DBMS
Secondary database modelsDocument 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
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.52
Rank#254  Overall
#39  Document stores
Score5.60
Rank#62  Overall
#35  Relational DBMS
Websitephoenix.apache.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerwww.percona.com/­mongodb/­software/­percona-server-for-mongodbwww.singlestore.com
Technical documentationphoenix.apache.orgspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.percona.com/­percona-distribution-for-mongodbdocs.singlestore.com
DeveloperApache Software FoundationSpotifyMicrosoftPerconaSingleStore Inc.
Initial release20142014201920152013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019cloud service with continuous releases3.4.10-2.10, November 20178.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source infoGPL Version 2commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJavaJavaC++C++, Go
Server operating systemsLinux
Unix
Windows
hostedLinuxLinux info64 bit version required
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.nonoyesnono
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedyesyes
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSONCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, RJavaScriptyes
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infovia In-Memory Engineyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAzure Active Directory AuthenticationAccess rights for users and rolesFine grained access control via users, groups and roles
More information provided by the system vendor
Apache PhoenixHeroicMicrosoft Azure Data ExplorerPercona Server for MongoDBSingleStore infoformer name was MemSQL
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
Apache PhoenixHeroicMicrosoft Azure Data ExplorerPercona Server for MongoDBSingleStore infoformer name was MemSQL
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