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DBMS > AnzoGraph DB vs. Hazelcast vs. Ingres vs. LevelDB vs. Microsoft Azure Data Explorer

System Properties Comparison AnzoGraph DB vs. Hazelcast vs. Ingres vs. LevelDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA widely adopted in-memory data gridWell established RDBMSEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesFully managed big data interactive analytics platform
Primary database modelGraph DBMS
RDF store
Key-value storeRelational DBMSKey-value storeRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitecambridgesemantics.com/­anzographhazelcast.comwww.actian.com/­databases/­ingresgithub.com/­google/­leveldbazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmhazelcast.org/­imdg/­docsdocs.actian.com/­ingresgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCambridge SemanticsHazelcastActian CorporationGoogleMicrosoft
Initial release201820081974 infooriginally developed at University Berkely in early 1970s20112019
Current release2.3, January 20215.3.6, November 202311.2, May 20221.23, February 2021cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemsLinuxAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Illumos
Linux
OS X
Windows
hosted
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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 infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availablenoyes
Secondary indexesnoyesyesnoall fields are automatically indexed
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query languageyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoEvent Listeners, Executor ServicesyesnoYes, possible languages: KQL, Python, R
Triggersnoyes infoEventsyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes infoReplicated MapIngres Replicatornoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlfine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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More resources
AnzoGraph DBHazelcastIngresLevelDBMicrosoft Azure Data Explorer
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