DBMS > CrateDB vs. eXtremeDB vs. MongoDB vs. Teradata Aster vs. Vertica
System Properties Comparison CrateDB vs. eXtremeDB vs. MongoDB vs. Teradata Aster vs. Vertica
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | CrateDB Xexclude from comparison | eXtremeDB Xexclude from comparison | MongoDB Xexclude from comparison | Teradata Aster Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | Natively in-memory DBMS with options for persistency, high-availability and clustering | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | Platform for big data analytics on multistructured data sources and types | 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 | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Relational DBMS Time Series DBMS | Document store | Relational DBMS | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Relational DBMS | Spatial DBMS Search engine integrated Lucene index, currently in MongoDB Atlas only. Time Series DBMS Time Series Collections introduced in Release 5.0 Vector DBMS currently available in the MongoDB Atlas cloud service only | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | www.mcobject.com | www.mongodb.com | www.vertica.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | www.mcobject.com/docs/extremedb.htm | www.mongodb.com/docs/manual | vertica.com/documentation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | McObject | MongoDB, Inc | Teradata | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2001 | 2009 | 2005 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.2, 2021 | 6.0.7, June 2023 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | commercial | Open Source MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available. | commercial | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no MongoDB available as DBaaS (MongoDB Atlas) | 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. | 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. |
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Implementation language | Java | C and C++ | C++ | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | AIX HP-UX Linux macOS Solaris Windows | Linux OS X Solaris Windows | Linux | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | yes | schema-free Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema. | Flexible Schema (defined schema, partial schema, schema free) defined schema within the relational store; partial schema or schema free in the Aster File Store | 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 string, integer, double, decimal, boolean, date, object_id, geospatial | 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 support of XML interfaces available | yes in Aster File Store | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | yes with the option: eXtremeSQL | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | .NET Client API JDBC JNI ODBC Proprietary protocol RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | ADO.NET JDBC ODBC OLE DB | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 C C# C++ Java Lua Python Scala | Actionscript unofficial driver C C# C++ Clojure unofficial driver ColdFusion unofficial driver D unofficial driver Dart unofficial driver Delphi unofficial driver Erlang Go Groovy unofficial driver Haskell Java JavaScript Kotlin Lisp unofficial driver Lua unofficial driver MatLab unofficial driver Perl PHP PowerShell unofficial driver Prolog unofficial driver Python R unofficial driver Ruby Rust Scala Smalltalk unofficial driver Swift | C C# C++ Java Python R | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | yes | JavaScript | R packages | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes by defining events | yes in MongoDB Atlas only | no | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | horizontal partitioning / sharding | Sharding Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime. | Sharding | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | Active Replication Fabric™ for IoT Multi-source replication by means of eXtremeDB Cluster option Source-replica replication by means of eXtremeDB High Availability option | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | yes Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured. | 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 | yes | yes SQL Map-Reduce Framework | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Immediate Consistency | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency or Eventual Consistency depending on configuration | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no typically not used, however similar functionality with DBRef possible | no | 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 | ACID | Multi-document ACID Transactions with snapshot isolation | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes Optimistic (MVCC) and pessimistic (locking) strategies available | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes optional, enabled by default | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes In-memory storage engine introduced with MongoDB version 3.2 | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | Access rights for users and roles | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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CrateDB | eXtremeDB | MongoDB | Teradata Aster | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | eXtremeDB databases can be modeled relationally or as objects and can utilize SQL... » more | Built around the flexible document data model and unified API, MongoDB is a developer... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,... » more | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,... » more | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | With hundreds of customers and over 30 million devices/applications using the product... » more | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | For server use cases, there is a simple per-server license irrespective of the number... » more | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | Cost-based models and subscription-based models are both available. One license is... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more Studio 3T: The world's favorite IDE for working with MongoDB » more Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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CrateDB | eXtremeDB | MongoDB | Teradata Aster | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Snowflake is the DBMS of the Year 2021 PostgreSQL is the DBMS of the Year 2020 PostgreSQL is the DBMS of the Year 2018 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT 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 Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO provided by Google News | McObject Delivers eXtremeDB 8.4 Improving Performance, Security, and Developer Productivity Latest embedded DBMS supports asymmetric multiprocessing systems McObject & IBM Set New Records for Speed & Stability in STAC-M3 Benchmark for Capital Markets The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less McObject’s new eXtremeDB Cluster provides distributed database solution for real-time apps provided by Google News | Analysts retool MongoDB stock price target after earnings Why MongoDB Stock Plunged Today MongoDB loses nearly a quarter of its value after adjusting revenue forecasts MongoDB shares sink 23% after management trims guidance Why MongoDB Stock Plunged Today provided by Google News | Northwestern Analytics Partners with Teradata Aster to Host Hackathon Teradata Aster gets graph database, HDFS-compatible file store Teradata Enhances Big Data Analytics Platform Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business Teradata's Aster shows how the flowers of fraud bloom provided by Google News | OCI Object Storage Completes Technical Validation of Vertica in Eon Mode Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services Postgres pioneer Michael Stonebraker promises to upend the database once more provided by Google News |
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