DBMS > eXtremeDB vs. Neo4j vs. Solr vs. Stardog vs. Vertica
System Properties Comparison eXtremeDB vs. Neo4j vs. Solr vs. Stardog vs. Vertica
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| Name | eXtremeDB Xexclude from comparison | Neo4j Xexclude from comparison | Solr Xexclude from comparison | Stardog Xexclude from comparison | Vertica  OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Natively in-memory DBMS with options for persistency, high-availability and clustering | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | A widely used distributed, scalable search engine based on Apache Lucene | Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS Time Series DBMS | Graph DBMS | Search engine | Graph DBMS RDF store | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Spatial DBMS | Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.mcobject.com | neo4j.com | solr.apache.org | www.stardog.com | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | www.mcobject.com/docs/extremedb.htm | neo4j.com/docs | solr.apache.org/resources.html | docs.stardog.com | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | McObject | Neo4j, Inc. | Apache Software Foundation | Stardog-Union | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2001 | 2007 | 2006 | 2010 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 8.2, 2021 | 5.19, April 2024 | 9.6.0, April 2024 | 7.3.0, May 2020 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source GPL version3, commercial licenses available | Open Source Apache Version 2 | commercial 60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C and C++ | Java, Scala | Java | Java | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | AIX HP-UX Linux macOS Solaris Windows | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | Linux macOS Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free and schema-optional | yes Dynamic Fields enables on-the-fly addition of new fields | schema-free and OWL/RDFS-schema support | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes supports customizable data types and automatic typing | 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 support of XML interfaces available | yes | no Import/export of XML data possible | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes pluggable indexing subsystem, by default Apache Lucene | yes All search fields are automatically indexed | yes supports real-time indexing in full-text and geospatial | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes with the option: eXtremeSQL | no | Solr Parallel SQL Interface | Yes, compatible with all major SQL variants through dedicated BI/SQL Server | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | .NET Client API JDBC JNI ODBC Proprietary protocol RESTful HTTP API | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | Java API RESTful HTTP/JSON API | GraphQL query language HTTP API Jena RDF API OWL RDF4J API Sesame REST HTTP Protocol SNARL SPARQL Spring Data Stardog Studio TinkerPop 3 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .Net C C# C++ Java Lua Python Scala | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | .Net Clojure Groovy Java JavaScript Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | yes User defined Procedures and Functions | Java plugins | user defined functions and aggregates, HTTP Server extensions in Java | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes by defining events | yes via event handler | yes User configurable commands triggered on index changes | yes via event handlers | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | horizontal partitioning / sharding | yes using Neo4j Fabric | Sharding | none | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Active Replication Fabric™ for IoT Multi-source replication by means of eXtremeDB Cluster optionSource-replica replication by means of eXtremeDB High Availability option | Causal Clustering using Raft protocol available in in Enterprise Version only | yes | Multi-source replication in HA-Cluster | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Eventual Consistency | Immediate Consistency in HA-Cluster | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | yes Relationships in graphs | no | yes relationships in graphs | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | optimistic locking | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes Optimistic (MVCC) and pessimistic (locking) strategies available | 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 | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | yes | Access rights for users and roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| eXtremeDB | Neo4j | Solr | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | eXtremeDB databases can be modeled relationally or as objects and can utilize SQL... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | With hundreds of customers and over 30 million devices/applications using the product... » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | For server use cases, there is a simple per-server license irrespective of the number... » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | This Week in Neo4j: Podcast, GraphRAG, GraphQL, Chatbot and more Neo4j Joins the Connect with Confluent Partner Program 10 Inspiring Projects to Spark Your NODES 2024 Presentation New Security Feature in Neo4j Aura: Customer Managed Keys Safeguarding Elections: How Graph Technology Powers Groundbreaking Research on Political Ads | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| eXtremeDB | Neo4j | Solr | Stardog | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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