DBMS > AnzoGraph DB vs. Ignite vs. Memcached vs. Microsoft Azure Data Explorer vs. PostgreSQL
System Properties Comparison AnzoGraph DB vs. Ignite vs. Memcached vs. Microsoft Azure Data Explorer vs. PostgreSQL
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Name | AnzoGraph DB Xexclude from comparison | Ignite Xexclude from comparison | Memcached Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization | Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale. | In-memory key-value store, originally intended for caching | Fully managed big data interactive analytics platform | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Key-value store Relational DBMS | Key-value store | Relational DBMS column oriented | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If 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 this 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 support 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 see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cambridgesemantics.com/anzograph | ignite.apache.org | www.memcached.org | azure.microsoft.com/services/data-explorer | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.cambridgesemantics.com/anzograph/userdoc/home.htm | apacheignite.readme.io/docs | github.com/memcached/memcached/wiki | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Cambridge Semantics | Apache Software Foundation | Danga Interactive originally developed by Brad Fitzpatrick for LiveJournal | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2018 | 2015 | 2003 | 2019 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 2.3, January 2021 | Apache Ignite 2.6 | 1.6.27, May 2024 | cloud service with continuous releases | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free trial version available | Open Source Apache 2.0 | Open Source BSD license | commercial | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++, Java, .Net | C | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux OS X Solaris Windows | FreeBSD Linux OS X Unix Windows | hosted | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Schema-free and OWL/RDFS-schema support | yes | schema-free | Fixed schema with schema-less datatypes (dynamic) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | no | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | no | yes | yes | yes specific XML-type available, but no XML query functionality. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | no | all fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SPARQL and SPARQL* as primary query language. Cypher preview. | ANSI-99 for query and DML statements, subset of DDL | no | Kusto Query Language (KQL), SQL subset | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Apache Mule gRPC JDBC Kafka OData access for BI tools OpenCypher RESTful HTTP API SPARQL | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | Proprietary protocol | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C++ Java Python | C# C++ Java PHP Python Ruby Scala | .Net C C++ ColdFusion Erlang Java Lisp Lua OCaml Perl PHP Python Ruby | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions and aggregates | yes (compute grid and cache interceptors can be used instead) | no | Yes, possible languages: KQL, Python, R | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes (cache interceptors and events) | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Automatic sharding | Sharding | none | Sharding Implicit feature of the cloud service | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication in MPP-Cluster | yes (replicated cache) | none Repcached, a Memcached patch, provides this functionallity | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Kerberos/HDFS data loading | yes (compute grid and hadoop accelerator) | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency in MPP-Cluster | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no not needed in graphs | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users and roles | Security Hooks for custom implementations | yes using SASL (Simple Authentication and Security Layer) protocol | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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AnzoGraph DB | Ignite | Memcached | Microsoft Azure Data Explorer | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Redis extends the lead in the DB-Engines key-value store ranking New DB-Engines Ranking shows the popularity of database management systems | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 AnzoGraph review: A graph database for deep analytics Cambridge Semantics Unveils AnzoGraph DB with Geospatial Analytics AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access Back to the future: Does graph database success hang on query language? provided by Google News GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 GridGain Showcases Power of Apache Ignite at Community Over Code Conference Apache Ignite: An Overview GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ... What is Apache Ignite? How is Apache Ignite Used? provided by Google News Why DDoS Threat Actors Are Shifting Their Tactics Intel Continues To Demonstrate The Importance Of Software Optimizations: Clear Linux + Xeon Max Benchmarks Why Redis beats Memcached for caching What are memcached servers, and why are they being used to launch record-setting DDoS attacks? Memcached DDoS: The biggest, baddest denial of service attacker yet provided by Google News We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL provided by Google News |
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