DBMS > Datastax Enterprise vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Neo4j vs. Teradata
System Properties Comparison Datastax Enterprise vs. GigaSpaces vs. Microsoft Azure Data Explorer vs. Neo4j vs. Teradata
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| Name | Datastax Enterprise Xexclude from comparison | GigaSpaces Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Neo4j Xexclude from comparison | Teradata Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions | 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 | A hybrid cloud data analytics software platform (Teradata Vantage) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Wide column store | Document store Object oriented DBMS  Values are user defined objects | Relational DBMS column oriented | Graph DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Graph DBMS Search engine | 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 engineTime Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.datastax.com/products/datastax-enterprise | www.gigaspaces.com | azure.microsoft.com/services/data-explorer | neo4j.com | www.teradata.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.datastax.com | docs.gigaspaces.com/latest/landing.html | docs.microsoft.com/en-us/azure/data-explorer | neo4j.com/docs | docs.teradata.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | DataStax | Gigaspaces Technologies | Microsoft | Neo4j, Inc. | Teradata | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2011 | 2000 | 2019 | 2007 | 1984 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 6.8, April 2020 | 15.5, September 2020 | cloud service with continuous releases | 5.19, April 2024 | Teradata Vantage 1.0 MU2, January 2019 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source Apache Version 2; Commercial licenses available | commercial | Open Source GPL version3, commercial licenses available | commercial | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. | Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Java | Java, C++, .Net | Java, Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X | Linux macOS Solaris Windows | hosted | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | hosted Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | schema-free | 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. | no | no XML can be used for describing objects metadata | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | all fields are automatically indexed | yes pluggable indexing subsystem, by default Apache Lucene | yes Join-index to prejoin tables, aggregate index, sparse index, hash index | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like DML and DDL statements (CQL); Spark SQL | SQL-99 for query and DML statements | Kusto Query Language (KQL), SQL subset | no | yes SQL 2016 + extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | GigaSpaces LRMI Hibernate JCache JDBC JPA ODBC RESTful HTTP API Spring Data | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | .NET Client API HTTP REST JDBC JMS Adapter ODBC OLE DB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | .Net C++ Java Python Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | C C++ Cobol Java (JDBC-ODBC) Perl PL/1 Python R Ruby | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | yes | Yes, possible languages: KQL, Python, R | yes User defined Procedures and Functions | yes UDFs, stored procedures, table functions in parallel | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | yes, event driven architecture | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes via event handler | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Sharding | Sharding Implicit feature of the cloud service | yes using Neo4j Fabric | Sharding Hashing | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | configurable replication factor, datacenter aware, advanced replication for edge computing | Multi-source replication synchronous or asynchronous Source-replica replication synchronous or asynchronous | 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 | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes Map-Reduce pattern can be built with XAP task executors | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Immediate Consistency Consistency level configurable: ALL, QUORUM, ANY | 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 | no | no | yes Relationships in graphs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | ACID | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Access rights for users can be defined per object | Role-based access control | Azure Active Directory Authentication | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Datastax Enterprise | GigaSpaces | Microsoft Azure Data Explorer | Neo4j | Teradata | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Supporting the following application requirements: Zero downtime - Built on Apache... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Annual subscription » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more GQL is Here: Your Cypher Queries in a GQL World GQL: The ISO Standard for Graphs Has Arrived What Is Retrieval-Augmented Generation (RAG)? This Week in Neo4j: Google Cloud, Analysis, Knowledge Graph, Relationships and more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Datastax Enterprise | GigaSpaces | Microsoft Azure Data Explorer | Neo4j | Teradata | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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