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DBMS > Datomic vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Yaacomo

System Properties Comparison Datomic vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Yaacomo

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonYaacomo  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.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Relational 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
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score0.18
Rank#314  Overall
#45  Key-value stores
#141  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorersqrrl.comyaacomo.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCognitectFairCom CorporationMicrosoftAmazon infooriginally Sqrrl Data, Inc.Q2WEB GmbH
Initial release20121979201920122009
Current release1.0.7180, July 2024V13, July 2024cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availablecommercialcommercialcommercial
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.
Implementation languageJava, ClojureANSI C, C++Java
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinuxAndroid
Linux
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes 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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.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
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Rno
TriggersBy using transaction functionsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoophorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of HadoopSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentnoAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnoyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
DatomicFaircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerSqrrlYaacomo
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