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DBMS > BigchainDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TimesTen

System Properties Comparison BigchainDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Teradata Aster vs. TimesTen

Editorial information provided by DB-Engines
NameBigchainDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTimesTen  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformPlatform for big data analytics on multistructured data sources and typesIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSRelational 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
Score0.85
Rank#208  Overall
#35  Document stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitewww.bigchaindb.comignite.apache.orgazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationbigchaindb.readthedocs.io/­en/­latestapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationMicrosoftTeradataOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20162015201920051998
Current releaseApache Ignite 2.6cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoAGPL v3Open Source infoApache 2.0commercialcommercialcommercial
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 languagePythonC++, Java, .Net
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hostedLinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)Flexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or datenoyesyes 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.noyesyesyes infoin Aster File Storeno
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyesyes
APIs and other access methodsCLI Client
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Haskell
Java
JavaScript
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Java
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RR packagesPL/SQL
Triggersyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes,with MongoDB ord RethinkDByesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesSecurity Hooks for custom implementationsAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BigchainDBIgniteMicrosoft Azure Data ExplorerTeradata AsterTimesTen
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