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DBMS > Google Cloud Bigtable vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. PouchDB

System Properties Comparison Google Cloud Bigtable vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. PouchDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platformJavaScript DBMS with an API inspired by CouchDB
Primary database modelKey-value store
Wide column store
Key-value storeRelational DBMSRelational DBMS infocolumn orientedDocument 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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitecloud.google.com/­bigtablehazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerpouchdb.com
Technical documentationcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerpouchdb.com/­guides
DeveloperGoogleHazelcastActian CorporationMicrosoftApache Software Foundation
Initial release201520081974 infooriginally developed at University Berkely in early 1970s20192012
Current release5.3.6, November 202311.2, May 2022cloud service with continuous releases7.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJavaScript
Server operating systemshostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or datenoyesyesyes 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 strategyno infobut tools for importing/exporting data from/to XML-files availableyesno
Secondary indexesnoyesyesall fields are automatically indexedyes infovia views
SQL infoSupport of SQLnoSQL-like query languageyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, RView functions in JavaScript
Triggersnoyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
Google Cloud BigtableHazelcastIngresMicrosoft Azure Data ExplorerPouchDB
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