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DBMS > Kdb vs. LMDB vs. Microsoft Azure Data Explorer vs. Redis

System Properties Comparison Kdb vs. LMDB vs. Microsoft Azure Data Explorer vs. Redis

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Editorial information provided by DB-Engines
NameKdb  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRedis  Xexclude from comparison
DescriptionHigh performance Time Series DBMSA high performant, light-weight, embedded key-value database libraryFully managed big data interactive analytics platformPopular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments infoRedis focuses on performance so most of its design decisions prioritize high performance and very low latencies.
Primary database modelTime Series DBMS
Vector DBMS
Key-value storeRelational DBMS infocolumn orientedKey-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence
Secondary database modelsRelational DBMSDocument 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
Document store infowith RedisJSON
Graph DBMS infowith RedisGraph
Spatial DBMS
Search engine infowith RediSearch
Time Series DBMS infowith RedisTimeSeries
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score1.94
Rank#120  Overall
#20  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score149.43
Rank#6  Overall
#1  Key-value stores
Websitekx.comwww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­services/­data-explorerredis.com
redis.io
Technical documentationcode.kx.comwww.lmdb.tech/­docdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.redis.com/­latest/­index.html
redis.io/­docs
DeveloperKx Systems, a division of First Derivatives plcSymasMicrosoftRedis project core team, inspired by Salvatore Sanfilippo infoDevelopment sponsored by Redis Inc.
Initial release2000 infokdb was released 2000, kdb+ in 2003201120192009
Current release3.6, May 20180.9.32, January 2024cloud service with continuous releases7.2.5, May 2024
License infoCommercial or Open Sourcecommercial infofree 32-bit versionOpen SourcecommercialOpen Source infosource-available extensions (modules), commercial licenses for Redis Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqCC
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Unix
Windows
hostedBSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.yesnoyesno
Secondary indexesyes infotable attribute 'grouped'noall fields are automatically indexedyes infowith RediSearch module
SQL infoSupport of SQLSQL-like query language (q)noKusto Query Language (KQL), SQL subsetwith RediSQL module
APIs and other access methodsHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol infoRESP - REdis Serialization Protocol
Supported programming languagesC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, RLua; Redis Functions coming in Redis 7 (slides and Github)
Triggersyes infowith viewsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicypublish/subscribe channels provide some trigger functionality; RedisGears
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneSharding infoImplicit feature of the cloud serviceSharding infoAutomatic hash-based sharding with support for hash-tags for manual sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkthrough RedisGears
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoAtomic execution of command blocks and scripts and optimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlrights management via user accountsnoAzure Active Directory AuthenticationAccess Control Lists (ACLs): redis.io/­docs/­management/­security/­acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/­docs/­management/­security/­encryption
Password-based authentication
More information provided by the system vendor
KdbLMDBMicrosoft Azure Data ExplorerRedis
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing modelsupon request
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More resources
KdbLMDBMicrosoft Azure Data ExplorerRedis
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