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DBMS > Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. SurrealDB

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Sphinx vs. Splice Machine vs. SurrealDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  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.Fully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelKey-value store
Wide column store
Relational DBMS infocolumn orientedSearch engineRelational DBMSDocument store
Graph 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
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websitecloud.google.com/­bigtableazure.microsoft.com/­services/­data-explorersphinxsearch.comsplicemachine.comsurrealdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docssplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperGoogleMicrosoftSphinx Technologies Inc.Splice MachineSurrealDB Ltd
Initial release20152019200120142022
Current releasecloud service with continuous releases3.5.1, February 20233.1, March 2021v1.5.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaRust
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyesschema-free
Typing infopredefined data types such as float or datenoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyesyes
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
Secondary indexesnoall fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yesSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnoyes infoJava
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory AuthenticationnoAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rules

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More resources
Google Cloud BigtableMicrosoft Azure Data ExplorerSphinxSplice MachineSurrealDB
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