DBMS > Couchbase vs. CrateDB vs. Microsoft Azure Synapse Analytics vs. RDFox vs. SingleStore
System Properties Comparison Couchbase vs. CrateDB vs. Microsoft Azure Synapse Analytics vs. RDFox vs. SingleStore
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Name | Couchbase Originally called Membase Xexclude from comparison | CrateDB Xexclude from comparison | Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse Xexclude from comparison | RDFox Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database | Distributed Database based on Lucene | Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server | High performance knowledge graph and semantic reasoning engine | 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 | Document store | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Relational DBMS | Graph DBMS RDF store | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Key-value store originating from the former Membase product and supporting the Memcached protocol Spatial DBMS using the Geocouch extension Search engine Time Series DBMS Vector DBMS | Relational DBMS | Relational DBMS | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.couchbase.com | cratedb.com | azure.microsoft.com/services/synapse-analytics | www.oxfordsemantic.tech | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.couchbase.com | cratedb.com/docs | docs.microsoft.com/azure/synapse-analytics | docs.oxfordsemantic.tech | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Couchbase, Inc. | Crate | Microsoft | Oxford Semantic Technologies | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2011 | 2013 | 2016 | 2017 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023 | 6.0, Septermber 2022 | 8.5, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Business Source License (BSL 1.1); Commercial licenses also available | Open Source | commercial | commercial | 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. | CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform. | 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 | C, C++, Go and Erlang | Java | C++ | C++ | C++, Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | hosted | Linux macOS Windows | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | Flexible Schema (defined schema, partial schema, schema free) | yes | yes RDF schemas | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes | 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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases | yes, but no triggers and constraints, and PostgreSQL compatibility | yes | no | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | CLI Client HTTP REST Kafka Connector Native language bindings for CRUD, Query, Search and Analytics APIs Spark Connector Spring Data | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | ADO.NET JDBC ODBC | RESTful HTTP API SPARQL 1.1 | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C Go Java JavaScript Node.js Kotlin PHP Python Ruby Scala | .NET Erlang Go community maintained client Java JavaScript (Node.js) community maintained client Perl community maintained client PHP Python R Ruby community maintained client Scala community maintained client | C# Java PHP | C Java | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Functions and timers in JavaScript and UDFs in Java, Python, SQL++ | user defined functions (Javascript) | Transact SQL | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes via the TAP protocol | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Automatic Sharding | Sharding | Sharding, horizontal partitioning | Sharding hash partitioning | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication including cross data center replication Source-replica replication | Configurable replication on table/partition-level | yes | replication via a shared file system | 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 | no | no can define user-defined aggregate functions for map-reduce-style calculations | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency selectable on a per-operation basis | Eventual Consistency Read-after-write consistency on record level | Immediate Consistency | Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | 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 Ephemeral buckets | no | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control. | rights management via user accounts | yes | Roles, resources, and access types | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Couchbase Originally called Membase | CrateDB | Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse | RDFox | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | F ree Tier and Enterprise Edition » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Couchbase Originally called Membase | CrateDB | Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse | RDFox | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems Swiss National Bank Sells 6100 Shares of Couchbase, Inc. (NASDAQ:BASE) Couchbase Announces New Features to Accelerate AI-Powered Adaptive Applications for Customers Couchbase's revenue grows 20% and its stock rises in extended trading Couchbase Server and Capella to gain vector support Insider Sale: Matthew Cain Sells 10,053 Shares of Couchbase Inc (BASE) provided by Google News CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Appoints Sergey Gerasimenko as New CTO How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge provided by Google News Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates Azure Synapse vs. Databricks: Data Platform Comparison 2024 Azure Synapse Link for Cosmos DB: New Analytics Capabilities provided by Google News Use semantic reasoning to infer new facts from your RDF graph by integrating RDFox with Amazon Neptune | Amazon ... The intuitions behind Knowledge Graphs and Reasoning | by Peter Crocker Financial Crime Discovery using Amazon EKS and Graph Databases | Amazon Web Services Top 9 Open Source Graph Databases Finding patterns with rules, using Knowledge Graphs and Semantic Reasoning | by Peter Crocker provided by Google News SingleStore CEO sees little future for purpose-built vector databases SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development Building a Modern Database: Nikita Shamgunov on Postgres and Beyond SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore update adds new tools to fuel GenAI, analytics provided by Google News |
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