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DBMS > Apache Pinot vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Titan

System Properties Comparison Apache Pinot vs. BigchainDB vs. Microsoft Azure Data Explorer vs. Titan

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonBigchainDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsFully managed big data interactive analytics platformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedGraph 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
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.85
Rank#208  Overall
#35  Document stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitepinot.apache.orgwww.bigchaindb.comazure.microsoft.com/­services/­data-explorergithub.com/­thinkaurelius/­titan
Technical documentationdocs.pinot.apache.orgbigchaindb.readthedocs.io/­en/­latestdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation and contributorsMicrosoftAurelius, owned by DataStax
Initial release2015201620192012
Current release1.0.0, September 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3commercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonJava
Server operating systemsAll OS with a Java JDK11 or higherLinuxhostedLinux
OS X
Unix
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCCLI Client
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesGo
Java
Python
Go
Haskell
Java
JavaScript
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoImplicit feature of the cloud serviceyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyesAzure Active Directory AuthenticationUser authentification and security via Rexster Graph Server

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More resources
Apache PinotBigchainDBMicrosoft Azure Data ExplorerTitan
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