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DBMS > Databricks vs. Fauna vs. Microsoft Azure Data Explorer vs. Tarantool vs. TerminusDB

System Properties Comparison Databricks vs. Fauna vs. Microsoft Azure Data Explorer vs. Tarantool vs. TerminusDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTarantool  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Fully managed big data interactive analytics platformIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelDocument store
Relational DBMS
Document store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
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
Spatial DBMS infowith Tarantool/GIS extensionDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Websitewww.databricks.comfauna.comazure.microsoft.com/­services/­data-explorerwww.tarantool.ioterminusdb.com
Technical documentationdocs.databricks.comdocs.fauna.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­docterminusdb.github.io/­terminusdb/­#
DeveloperDatabricksFauna, Inc.MicrosoftVKDataChemist Ltd.
Initial release20132014201920082018
Current releasecloud service with continuous releases2.10.0, May 202211.0.0, January 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++Prolog, Rust
Server operating systemshostedhostedhostedBSD
Linux
macOS
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeFixed schema with schema-less datatypes (dynamic)Flexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
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-typesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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.yesnoyesnono
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLnoKusto Query Language (KQL), SQL subsetFull-featured ANSI SQL supportSQL-like query language (WOQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesPython
R
Scala
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsYes, possible languages: KQL, Python, RLua, C and SQL stored proceduresyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingSharding infoImplicit feature of the cloud serviceSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Graph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Casual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlIdentity management, authentication, and access controlAzure Active Directory AuthenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Role-based access control
More information provided by the system vendor
DatabricksFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerTarantoolTerminusDB infoformer name was DataChemist
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFauna infopreviously named FaunaDBMicrosoft Azure Data ExplorerTarantoolTerminusDB infoformer name was DataChemist
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