DBMS > IBM Db2 vs. InfluxDB vs. Microsoft Azure Data Explorer vs. SingleStore vs. TypeDB
System Properties Comparison IBM Db2 vs. InfluxDB vs. Microsoft Azure Data Explorer vs. SingleStore vs. TypeDB
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Name | IBM Db2 formerly named DB2 or IBM Database 2 Xexclude from comparison | InfluxDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | TypeDB formerly named Grakn Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Common in IBM host environments, 2 different versions for host and Windows/Linux | DBMS for storing time series, events and metrics | Fully managed big data interactive analytics platform | 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 | TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS Since Version 10.5 support for JSON/BSON documents compatible with MongoDB | Time Series DBMS | Relational DBMS column oriented | Relational DBMS | Graph DBMS Relational DBMS Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store RDF store in Db2 LUW (Linux, Unix, Windows) Spatial DBMS with Db2 Spatial Extender | Spatial DBMS with GEO package | 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 Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.ibm.com/products/db2 | www.influxdata.com/products/influxdb-overview | azure.microsoft.com/services/data-explorer | www.singlestore.com | typedb.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.ibm.com/docs/en/db2 | docs.influxdata.com/influxdb | docs.microsoft.com/en-us/azure/data-explorer | docs.singlestore.com | typedb.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | IBM | Microsoft | SingleStore Inc. | Vaticle | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 1983 host version | 2013 | 2019 | 2013 | 2016 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 12.1, October 2016 | 2.7.6, April 2024 | cloud service with continuous releases | 8.5, January 2024 | 2.26.3, January 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial free version is available | Open Source MIT-License; commercial enterprise version available | commercial | commercial free developer edition available | Open Source GPL Version 3, commercial licenses 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. | 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 and C++ | Go | C++, Go | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX HP-UX Linux Solaris Windows z/OS | Linux OS X through Homebrew | hosted | Linux 64 bit version required | Linux OS X Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | Fixed schema with schema-less datatypes (dynamic) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | Numeric data and Strings | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | 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 | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | SQL-like query language | Kusto Query Language (KQL), SQL subset | yes but no triggers and foreign keys | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC JSON style queries MongoDB compatible ODBC XQuery | HTTP API JSON over UDP | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | gRPC protocol TypeDB Console (shell) TypeDB Studio (Visualisation software- previously TypeDB Workbase) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Cobol Delphi Fortran Java Perl PHP Python Ruby Visual Basic | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | Bash C C# Java JavaScript (Node.js) Python | All JVM based languages Groovy Java JavaScript (Node.js) Python Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | Yes, possible languages: KQL, Python, R | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding only with Windows/Unix/Linux Version | Sharding in enterprise version only | Sharding Implicit feature of the cloud service | Sharding hash partitioning | Sharding by using Cassandra | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes with separate tools (MQ, InfoSphere) | selectable replication factor in enterprise version only | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication stores two copies of each physical data partition on two separate nodes | Multi-source replication by using Cassandra | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no can define user-defined aggregate functions for map-reduce-style calculations | yes by using Apache Kafka and Apache Zookeeper | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | no | no | no substituted by the relationship feature | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, multi-version concurrency control (MVCC) | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | 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. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes Depending on used storage engine | no | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | simple rights management via user accounts | Azure Active Directory Authentication | Fine grained access control via users, groups and roles | yes at REST API level; other APIs in progress | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IBM Db2 formerly named DB2 or IBM Database 2 | InfluxDB | Microsoft Azure Data Explorer | SingleStore former name was MemSQL | TypeDB formerly named Grakn | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed... » more | TypeDB is a polymorphic database with a conceptual data model, a strong subtyping... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | SingleStore’s competitive advantages include: Easy and Simplified Architecture with... » more | TypeDB provides a new level of expressivity, extensibility, interoperability, and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting... » more | Life sciences : TypeDB makes working with biological data much easier and accelerates... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | Customers in various industries worldwide including US and International Industry... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | F ree Tier and Enterprise Edition » more | Apache f or language drivers, and AGPL and Commercial for the database server. The... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | An Introductory Guide to Grafana Alerts What is DevRel at InfluxData What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg Converting Timestamp to Date in Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IBM Db2 formerly named DB2 or IBM Database 2 | InfluxDB | Microsoft Azure Data Explorer | SingleStore former name was MemSQL | TypeDB formerly named Grakn | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Simplify workload management and cloud provisioning with Amazon RDS for Db2’s consumption-based licensing Data migration strategies to Amazon RDS for Db2 | Amazon Web Services IBM's vintage Db2 database jumps on AWS's cloud bandwagon Precisely says it's smoothing migration of Db2 analytics data to AWS cloud – Blocks and Files How Amazon RDS for IBM Db2 Showcases the Power of Co-Creation provided by Google News | Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ... Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services 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 | 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 Announcing watsonx.ai and SingleStore for generative AI applications provided by Google News | An Enterprise Data Stack Using TypeDB | by Daniel Crowe Speedb Goes Open Source With Its Speedb Data Engine, A Drop-in Replacement for RocksDB 195 Data Science Libraries You Should Reconsider Using | by Dimitris Effrosynidis Modelling Biomedical Data for a Drug Discovery Knowledge Graph How Roche Discovered Novel Potential Gene Targets with TypeDB provided by Google News |
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