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DBMS > Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer vs. Sqrrl vs. YugabyteDB

System Properties Comparison Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer vs. Sqrrl vs. YugabyteDB

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonYugabyteDB  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.
DescriptionA widely adopted in-memory data gridTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelKey-value storeTime Series DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
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
Document store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websitehazelcast.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorersqrrl.comwww.yugabyte.com
Technical documentationhazelcast.org/­imdg/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperHazelcastSpotifyMicrosoftAmazon infooriginally Sqrrl Data, Inc.Yugabyte Inc.
Initial release20082014201920122017
Current release5.3.6, November 2023cloud service with continuous releases2.19, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
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.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageJavaJavaJavaC and C++
Server operating systemsAll OS with a Java VMhostedLinuxLinux
OS X
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freedepending on used data model
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.yes infothe object must implement a serialization strategynoyesno
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetnoyes, PostgreSQL compatible
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languages.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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoYes, possible languages: KQL, Python, Rnoyes infosql, plpgsql, C
Triggersyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of HadoopBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoAtomic updates per row, document, or graph entityDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlRole-based access controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)yes
More information provided by the system vendor
HazelcastHeroicMicrosoft Azure Data ExplorerSqrrlYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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HazelcastHeroicMicrosoft Azure Data ExplorerSqrrlYugabyteDB
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