DBMS > CrateDB vs. Microsoft Azure Data Explorer vs. Teradata vs. Virtuoso vs. YugabyteDB
System Properties Comparison CrateDB vs. Microsoft Azure Data Explorer vs. Teradata vs. Virtuoso vs. YugabyteDB
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Name | CrateDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Teradata Xexclude from comparison | Virtuoso Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | Fully managed big data interactive analytics platform | A hybrid cloud data analytics software platform (Teradata Vantage) | Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Relational DBMS column oriented | Relational DBMS | Document store Graph DBMS Native XML DBMS Relational DBMS RDF store Search engine | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Relational DBMS | 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 Graph DBMS Spatial DBMS Time Series DBMS | Spatial DBMS | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | azure.microsoft.com/services/data-explorer | www.teradata.com | virtuoso.openlinksw.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | docs.microsoft.com/en-us/azure/data-explorer | docs.teradata.com | docs.openlinksw.com/virtuoso | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | Microsoft | Teradata | OpenLink Software | Yugabyte Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2019 | 1984 | 1998 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | Teradata Vantage 1.0 MU2, January 2019 | 7.2.11, September 2023 | 2.19, September 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | commercial | commercial | Open Source GPLv2, extended commercial license available | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | 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. | YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C | C and C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | hosted | hosted Linux | AIX FreeBSD HP-UX Linux OS X Solaris Windows | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | Fixed schema with schema-less datatypes (dynamic) | yes | yes SQL - Standard relational schema RDF - Quad (S, P, O, G) or Triple (S, P, O) XML - DTD, XML Schema DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | 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 | 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 | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | all fields are automatically indexed | yes Join-index to prejoin tables, aggregate index, sparse index, hash index | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | Kusto Query Language (KQL), SQL subset | yes SQL 2016 + extensions | yes SQL-92, SQL-200x, SQL-3, SQLX | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | .NET Client API HTTP REST JDBC JMS Adapter ODBC OLE DB | ADO.NET GeoSPARQL HTTP API JDBC Jena RDF API ODBC OLE DB RDF4J API RESTful HTTP API Sesame REST HTTP Protocol SOAP webservices SPARQL 1.1 WebDAV XPath XQuery XSLT | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .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 | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C++ Cobol Java (JDBC-ODBC) Perl PL/1 Python R Ruby | .Net C C# C++ Java JavaScript Perl PHP Python Ruby Visual Basic | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | Yes, possible languages: KQL, Python, R | yes UDFs, stored procedures, table functions in parallel | yes Virtuoso PL | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding Implicit feature of the cloud service | Sharding Hashing | yes | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-source replication Source-replica replication | Chain, star, and bi-directional replication Multi-source replication Source-replica replication | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | no | ACID | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | Microsoft Azure Data Explorer | Teradata | Virtuoso | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations... » more | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,... » more | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | Broad use across enterprises and governments including — European Union (EU) US Government... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform... » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature... » more | Apache 2.0 license for the database » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | Microsoft Azure Data Explorer | Teradata | Virtuoso | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Teradata is the most popular data warehouse DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Partners with HiveMQ to Advance IoT Data Management and Analytics Across Industries How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions Crate.io raises $10M to grow its database platform provided by Google News | Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services Log and Telemetry Analytics Performance Benchmark provided by Google News | Truist Financial Corp Reduces Position in Teradata Co. (NYSE:TDC) Bear of the Day: Teradata (TDC) Teradata Stockholders Approve Incentive Plan and Elect Directors Dynamic Technology Lab Private Ltd Makes New Investment in Teradata Co. (NYSE:TDC) Prepare and load Amazon S3 data into Teradata using AWS Glue through its native connector for Teradata Vantage ... provided by Google News | Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark The surprising link between Formula One and enterprise PostgreSQL optimisation YugabyteDB Managed Introduces Product Labs Experience for Immersive Distributed SQL Learning Can Yugabyte Become The Defacto Database For Large-Scale, Cloud Native Applications? provided by Google News |
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