DBMS > Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Neo4j vs. SingleStore
System Properties Comparison Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Neo4j vs. SingleStore
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Name | Hazelcast Xexclude from comparison | Ingres Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Neo4j Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A widely adopted in-memory data grid | Well established RDBMS | Fully managed big data interactive analytics platform | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store | Relational DBMS | Relational DBMS column oriented | Graph DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store JSON support with IMDG 3.12 | 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 Spatial DBMS Time Series DBMS Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | hazelcast.com | www.actian.com/databases/ingres | azure.microsoft.com/services/data-explorer | neo4j.com | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | hazelcast.org/imdg/docs | docs.actian.com/ingres | docs.microsoft.com/en-us/azure/data-explorer | neo4j.com/docs | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Hazelcast | Actian Corporation | Microsoft | Neo4j, Inc. | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 1974 originally developed at University Berkely in early 1970s | 2019 | 2007 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.3.6, November 2023 | 11.2, May 2022 | cloud service with continuous releases | 5.20, May 2024 | 8.5, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; commercial licenses available | commercial | commercial | Open Source GPL version3, commercial licenses available | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C | Java, Scala | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM | AIX HP Open VMS HP-UX Linux Solaris Windows | hosted | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | Fixed schema with schema-less datatypes (dynamic) | schema-free and schema-optional | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | 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. | yes the object must implement a serialization strategy | no but tools for importing/exporting data from/to XML-files available | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | all fields are automatically indexed | yes pluggable indexing subsystem, by default Apache Lucene | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | yes | Kusto Query Language (KQL), SQL subset | no | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | 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 | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph Mapper RESTful HTTP API Spring Data Neo4j TinkerPop 3 | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C# C++ Clojure Go Java JavaScript (Node.js) Python Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | Bash C C# Java JavaScript (Node.js) Python | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes Event Listeners, Executor Services | yes | Yes, possible languages: KQL, Python, R | yes User defined Procedures and Functions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes Events | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes via event handler | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | horizontal partitioning Ingres Star to access multiple databases simultaneously | Sharding Implicit feature of the cloud service | yes using Neo4j Fabric | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes Replicated Map | Ingres Replicator | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency or Eventual Consistency selectable by user Raft Consensus Algorithm | Immediate Consistency | Eventual Consistency Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes Relationships in graphs | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | one or two-phase-commit; repeatable reads; read commited | ACID | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes MVCC | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Role-based access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Hazelcast | Ingres | Microsoft Azure Data Explorer | Neo4j | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Neo4j is the market leader, graph database category creator, and the most widely... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more openCypher Will Pave the Road to GQL for Cypher Implementers 7 Tips for Submitting Your NODES 2024 Talk | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Hazelcast | Ingres | Microsoft Azure Data Explorer | Neo4j | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Applying Graph Analytics to Game of Thrones MySQL, PostgreSQL and Redis are the winners of the March ranking The openCypher Project: Help Shape the SQL for Graphs | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Hazelcast Weaves Wider Logic Threads Through The Data Fabric Hazelcast 5.4 real time data processing platform boosts AI and consistency Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit Real-Time Data Platform Hazelcast Introduces New Chief Technology Officer Adrian Soars Hazelcast: The 'true' value of streaming real-time data provided by Google News Actian Launches Ingres 12.0 Database Postgres pioneer Michael Stonebraker promises to upend the database once more New startup from Postgres creator puts the database at heart of software stack PostgreSQL now top developer choice ahead of MySQL, according to massive new survey • DEVCLASS Dr. Michael Stonebraker: A Short History of Database Systems 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 New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates Public Preview: Azure Data Explorer Add-On for Splunk | Azure updates provided by Google News Neo4j & Snowflake Collaborate for AI Insights & Analytics Neo4j integrates dozens of graph analytics functions with data in Snowflake Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Neo4j Empowers Syracuse University with $250K Grant to Tackle Misinformation in 2024 Elections Neo4j partners with Snowflake to enhance data science in cloud provided by Google News Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps Announcing watsonx.ai and SingleStore for generative AI applications provided by Google News |
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