DBMS > Amazon Neptune vs. Datastax Enterprise vs. InterSystems Caché vs. PostgreSQL vs. Weaviate
System Properties Comparison Amazon Neptune vs. Datastax Enterprise vs. InterSystems Caché vs. PostgreSQL vs. Weaviate
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Amazon Neptune Xexclude from comparison | Datastax Enterprise Xexclude from comparison | InterSystems Caché Xexclude from comparison | PostgreSQL Xexclude from comparison | Weaviate Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fast, reliable graph database built for the cloud | 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. | A multi-model DBMS and application server | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | An AI-native realtime vector database engine that integrates scalable machine learning models. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Graph DBMS RDF store | Wide column store | Key-value store Object oriented DBMS Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Vector DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Document store | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/neptune | www.datastax.com/products/datastax-enterprise | www.intersystems.com/products/cache | www.postgresql.org | github.com/weaviate/weaviate weaviate.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | aws.amazon.com/neptune/developer-resources | docs.datastax.com | docs.intersystems.com | www.postgresql.org/docs | weaviate.io/developers/weaviate | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | DataStax | InterSystems | PostgreSQL Global Development Group www.postgresql.org/developer | Weaviate B.V. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2017 | 2011 | 1997 | 1989 1989: Postgres, 1996: PostgreSQL | 2019 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 6.8, April 2020 | 2018.1.4, May 2020 | 16.3, May 2024 | 1.19, May 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | commercial | Open Source BSD | Open Source commercial license available with Weaviate Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | 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. |
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Implementation language | Java | C | Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X | AIX HP Open VMS HP-UX Linux OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | depending on used data model | yes | yes, maps to GraphQL interface | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | yes | yes string, int, float, geo point, date, cross reference, fuzzy references | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | yes | yes specific XML-type available, but no XML query functionality. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | yes | yes | yes all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | SQL-like DML and DDL statements (CQL); Spark SQL | yes | yes standard with numerous extensions | GraphQL is used as query language | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | OpenCypher RDF 1.1 / SPARQL 1.1 TinkerPop Gremlin | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | .NET Client API JDBC ODBC RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | GraphQL query language RESTful HTTP/JSON API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# Go Java JavaScript PHP Python Ruby Scala | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | C# C++ Java | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | JavaScript / TypeScript Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | none | Sharding no "single point of failure" | none | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances. | configurable replication factor, datacenter aware, advanced replication for edge computing | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Immediate Consistency | Immediate Consistency | Eventual Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes Relationships in graphs | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no Atomicity and isolation are supported for single operations | ACID | ACID | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes with encyption-at-rest | 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 and roles can be defined via the AWS Identity and Access Management (IAM) | Access rights for users can be defined per object | Access rights for users, groups and roles | fine grained access rights according to SQL-standard | API Keys OpenID Connect Discovery | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Neptune | Datastax Enterprise | InterSystems Caché | PostgreSQL | Weaviate | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | Weaviate is an open source vector database that is robust, scalable, cloud-native,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Supporting the following application requirements: Zero downtime - Built on Apache... » more | Flexible deployment - Free, open source or fully-managed cloud vector database service... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Applications that must be massively and linearly scalable with 100% uptime and able... » more | As a database supporting the development of generative AI and semantic search applications... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | All companies that have data. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Annual subscription » more | Weaviate is open-source, and free to use. Weaviate is also available as a fully managed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Amazon Neptune | Datastax Enterprise | InterSystems Caché | PostgreSQL | Weaviate | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 | Weaviate, an ANN Database with CRUD support AWS Weekly Roundup: LlamaIndex support for Amazon Neptune, force AWS CloudFormation stack deletion, and more ... Amazon Neptune Analytics is now available in the AWS Europe (London) Region Amazon Neptune Analytics is now generally available Analyze large amounts of graph data to get insights and find trends with Amazon Neptune Analytics | Amazon Web ... Amazon Neptune announces support for data APIs in the AWS SDK provided by Google News DataStax previews new Hyper Converged Data Platform for enterprise AI DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite ... How to Migrate From DataStax Enterprise to Instaclustr Managed Apache Cassandra DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech provided by Google News AWS, GCP, Oracle, Azure, SAP Lead Cloud DBMS Market: Gartner Associative Data Modeling Demystified - Part1 - DataScienceCentral.com Announcing IBM Spectrum Sentinel: Building a Cyber Resilient Future Choosing a Database Technology. A roadmap and process overview | by Shirish Joshi Nearly three years on from Cambridge's Epic go-live provided by Google News How to implement a better like, views, comment counters in PostgreSQL? Automatically Generate Types for Your PostgreSQL Database First Principles: Optimizing PostgreSQL for the cloud Oracle Introduces PostgreSQL Running Native on OCI General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector ... Foley Represents Cortical Ventures in $50M Series B Round for Weaviate Weaviate Strengthens Partnership with AWS to Make it Easier for Developers to Build Generative AI Applications Getting Started with Weaviate: A Beginner's Guide to Search with Vector Databases Weaviate Raises $50 Million Series B Funding to Meet Soaring Demand for AI Native Vector Database Technology ... provided by Google News |
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