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DBMS > EventStoreDB vs. Microsoft Azure Data Explorer vs. Riak TS vs. Tarantool vs. TerminusDB

System Properties Comparison EventStoreDB vs. Microsoft Azure Data Explorer vs. Riak TS vs. Tarantool vs. TerminusDB

Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak TS  Xexclude from comparisonTarantool  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Fully managed big data interactive analytics platformRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVIn-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 modelEvent StoreRelational DBMS infocolumn orientedTime Series DBMSDocument 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
Score1.19
Rank#173  Overall
#1  Event Stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.28
Rank#307  Overall
#27  Time Series 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.eventstore.comazure.microsoft.com/­services/­data-explorerwww.tarantool.ioterminusdb.com
Technical documentationdevelopers.eventstore.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­ts/­latestwww.tarantool.io/­en/­docterminusdb.github.io/­terminusdb/­#
DeveloperEvent Store LimitedMicrosoftOpen Source, formerly Basho TechnologiesVKDataChemist Ltd.
Initial release20122019201520082018
Current release21.2, February 2021cloud service with continuous releases3.0.0, September 20222.10.0, May 202211.0.0, January 2023
License infoCommercial or Open SourceOpen SourcecommercialOpen SourceOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangC and C++Prolog, Rust
Server operating systemsLinux
Windows
hostedLinux
OS X
BSD
Linux
macOS
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnostring, 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.yesnonono
Secondary indexesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes, limitedFull-featured ANSI SQL supportSQL-like query language (WOQL)
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Open binary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
JavaScript
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RErlangLua, C and SQL stored proceduresyes
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingSharding, 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 nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factorAsynchronous 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 methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyCasual 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 integritynono infolinks between datasets can be storedyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, 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.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAzure Active Directory AuthenticationnoAccess 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

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More resources
EventStoreDBMicrosoft Azure Data ExplorerRiak TSTarantoolTerminusDB infoformer name was DataChemist
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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