DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Google Cloud Bigtable vs. Graph Engine vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Prometheus

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Prometheus

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPrometheus  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA widely adopted in-memory data gridFully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring system
Primary database modelKey-value store
Wide column store
Graph DBMS
Key-value store
Key-value storeRelational DBMS infocolumn orientedTime Series 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
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
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitecloud.google.com/­bigtablewww.graphengine.iohazelcast.comazure.microsoft.com/­services/­data-explorerprometheus.io
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docs
DeveloperGoogleMicrosoftHazelcastMicrosoft
Initial release20152010200820192015
Current release5.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0
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 language.NET and CJavaGo
Server operating systemshosted.NETAll OS with a Java VMhostedLinux
Windows
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
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-typesNumeric data only
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.nonoyes infothe object must implement a serialization strategyyesno infoImport of XML data possible
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLnonoSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresnoyesyes 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 nodesShardinghorizontal partitioningShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
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 AlgorithmEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlAzure Active Directory Authenticationno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google Cloud BigtableGraph Engine infoformer name: TrinityHazelcastMicrosoft Azure Data ExplorerPrometheus
Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database
6 May 2015, TechCrunch

provided by Google News

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

provided by Google News

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast appoints Anthony Griffin as Chief Architect -
11 June 2024, Enterprise Times

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast Achieves Record Year with Leading Brands Choosing Its Platform for Application Modernization, AI Initiatives
22 February 2024, Datanami

Hazelcast Versus Redis: A Practical Comparison
4 January 2024, Database Trends and Applications

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview)
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink
8 January 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, Microsoft

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, Microsoft

provided by Google News

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

Exadata Real-Time Insight - Quick Start
3 April 2024, Oracle

OpenTelemetry vs. Prometheus: You can’t fix what you can’t see
29 March 2024, IBM

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here