DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > BoltDB vs. Datomic vs. Heroic vs. Microsoft Azure Data Explorer vs. Vertica

System Properties Comparison BoltDB vs. Datomic vs. Heroic vs. Microsoft Azure Data Explorer vs. Vertica

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDatomic  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedRelational DBMS infoColumn oriented
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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.datomic.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationdocs.datomic.comspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperCognitectSpotifyMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20132012201420192005
Current release1.0.6735, June 2023cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infolimited edition freeOpen Source infoApache 2.0commercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, ClojureJavaC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyesyesyes 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.nononoyesno
Secondary indexesnoyesyes infovia Elasticsearchall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnononoKusto Query Language (KQL), SQL subsetFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIHQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsnoYes, possible languages: KQL, Python, Ryes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoBy using transaction functionsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnonono
User concepts infoAccess controlnonoAzure Active Directory Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BoltDBDatomicHeroicMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BoltDBDatomicHeroicMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
Recent citations in the news

What I learnt from building 3 high traffic web applications on an embedded key value store.
21 February 2018, hackernoon.com

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

Three Reasons DevOps Should Consider Rocky Linux 9.4
15 May 2024, DevOps.com

Roblox’s cloud-native catastrophe: A post mortem
31 January 2022, InfoWorld

How to Put a GUI on Ansible, Using Semaphore
22 April 2023, The New Stack

provided by Google News

Nubank buys firm behind Clojure programming language
28 July 2020, Finextra

Zoona Case Study
16 December 2017, AWS Blog

Architecting Software for Leverage
13 November 2021, InfoQ.com

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Brazil’s Nubank acquires US software firm Cognitect, creator of Clojure and Datomic
24 July 2020, LatamList

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

provided by Google News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

How Embedded Analytics Help ISVs Overcome Challenges
14 September 2023, Spiceworks News and Insights

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

OpenText integrates Micro Focus tech through Cloud Editions 23.3
26 July 2023, Techzine Europe

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Present your product here