DBMS > CrateDB vs. MongoDB vs. SingleStore vs. Solr vs. TimescaleDB
System Properties Comparison CrateDB vs. MongoDB vs. SingleStore vs. Solr vs. TimescaleDB
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Name | CrateDB Xexclude from comparison | MongoDB Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | Solr Xexclude from comparison | TimescaleDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure | 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 | A widely used distributed, scalable search engine based on Apache Lucene | A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Document store | Relational DBMS | Search engine | Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Document store Spatial DBMS Time Series DBMS Vector DBMS | Spatial DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | www.mongodb.com | www.singlestore.com | solr.apache.org | www.timescale.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | www.mongodb.com/docs/manual | docs.singlestore.com | solr.apache.org/resources.html | docs.timescale.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | MongoDB, Inc | SingleStore Inc. | Apache Software Foundation | Timescale | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2009 | 2013 | 2006 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 6.0.7, June 2023 | 8.5, January 2024 | 9.5.0, February 2024 | 2.13.0, November 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | 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 free developer edition available | Open Source Apache Version 2 | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no MongoDB available as DBaaS (MongoDB Atlas) | 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. | MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. | 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 | Java | C++ | C++, Go | Java | C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux OS X Solaris Windows | Linux 64 bit version required | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | Linux OS X Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | 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. | yes | yes Dynamic Fields enables on-the-fly addition of new fields | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes string, integer, double, decimal, boolean, date, object_id, geospatial | yes | yes supports customizable data types and automatic typing | numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes All search fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | Read-only SQL queries via the MongoDB Atlas SQL Interface | yes but no triggers and foreign keys | Solr Parallel SQL Interface | yes full PostgreSQL SQL syntax | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | GraphQL HTTP REST Prisma proprietary protocol using JSON | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | Java API RESTful HTTP/JSON API | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | 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 | Bash C C# Java JavaScript (Node.js) Python | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | .Net C C++ Delphi Java JDBC JavaScript Perl PHP Python R Ruby Scheme Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | JavaScript | yes | Java plugins | user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes in MongoDB Atlas only | no | yes User configurable commands triggered on index changes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | 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 hash partitioning | Sharding | yes, across time and space (hash partitioning) attributes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | Multi-Source deployments with MongoDB Atlas Global Clusters Source-replica replication | Source-replica replication stores two copies of each physical data partition on two separate nodes | yes | Source-replica replication with hot standby and reads on replicas | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no can define user-defined aggregate functions for map-reduce-style calculations | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Eventual Consistency can be individually decided for each read operation Immediate Consistency default behaviour | Immediate Consistency | Eventual Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no typically not used, however similar functionality with DBRef possible | no | 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 | Multi-document ACID Transactions with snapshot isolation | ACID | optimistic locking | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes, multi-version concurrency control (MVCC) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes optional, enabled by default | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes In-memory storage engine introduced with MongoDB version 3.2 | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | Access rights for users and roles | Fine grained access control via users, groups and roles | yes | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | MongoDB | SingleStore former name was MemSQL | Solr | TimescaleDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | MongoDB provides an integrated suite of cloud database and data services to accelerate... » 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 | Built around the flexible document data model and unified API, MongoDB is a developer... » 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 | AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of... » 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 | ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,... » 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 | Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month... » more | Customers in various industries worldwide including US and International Industry... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses... » more | F ree Tier and Enterprise Edition » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | MongoDB | SingleStore former name was MemSQL | Solr | TimescaleDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | 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 Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO CrateDB 4.5 takes distributed SQL database open source provided by Google News | Decoding 26 Analyst Evaluations For MongoDB - MongoDB (NASDAQ:MDB) MongoDB (NASDAQ:MDB) Price Target Increased to $500.00 by Analysts at Tigress Financial How to Build Your Own RAG System With LlamaIndex and MongoDB MongoDB: The Future Propelled By Atlas Cloud Database (NASDAQ:MDB) MongoDB, Inc. (MDB) Is a Trending Stock: Facts to Know Before Betting on It provided by Google News | SingleStore CEO sees little future for purpose-built vector databases SingleStore adds indexed vector search to Pro Max release for faster AI work – Blocks and Files SingleStore Announces Real-time Data Platform to Further Accelerate AI, Analytics and Application Development SingleStore CEO on High-Speed Database Currents SingleStore, Snowflake Help Customers Build Enterprise-Ready Generative AI Apps provided by Google News | SOLR-led walkout demands better conditions for Compass workers (SOLR) Trading Signals Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ... SOLR hosts teach-in of labor movements at Northwestern Top 5 stock gainers and losers: SOLR.V, GRSL.V, ANON.C provided by Google News | TimescaleDB Is a Vector Database Now, Too Timescale Launches Dynamic PostgreSQL, the Cost-Effective Alternative to Serverless and Peak-Allocation Pay Models Timescale Introduces Dynamic PostgreSQL, an Alternative to Serverless Databases Visualizing IoT Data at Scale With Hopara and TimescaleDB Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL provided by Google News |
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