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DBMS > eXtremeDB vs. Google Cloud Bigtable vs. Graphite vs. H2 vs. Microsoft Azure Data Explorer

System Properties Comparison eXtremeDB vs. Google Cloud Bigtable vs. Graphite vs. H2 vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGraphite  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Fully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Wide column store
Time Series DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSDocument 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
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.mcobject.comcloud.google.com/­bigtablegithub.com/­graphite-project/­graphite-webwww.h2database.comazure.microsoft.com/­services/­data-explorer
Technical documentationwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docsgraphite.readthedocs.iowww.h2database.com/­html/­main.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperMcObjectGoogleChris DavisThomas MuellerMicrosoft
Initial release20012015200620052019
Current release8.2, 20212.2.220, July 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++PythonJava
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
Unix
All OS with a Java VMhosted
Data schemeyesschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoNumeric data onlyyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.no infosupport of XML interfaces availablenononoyes
Secondary indexesyesnonoyesall fields are automatically indexed
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnonoyesKusto Query Language (KQL), SQL subset
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Sockets
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnonoJava Stored Procedures and User-Defined FunctionsYes, possible languages: KQL, Python, R
Triggersyes infoby defining eventsnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingShardingnonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Internal replication in Colossus, and regional replication between two clusters in different zonesnoneWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes infolockingyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardAzure Active Directory Authentication
More information provided by the system vendor
eXtremeDBGoogle Cloud BigtableGraphiteH2Microsoft Azure Data Explorer
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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eXtremeDBGoogle Cloud BigtableGraphiteH2Microsoft Azure Data Explorer
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