DBMS > CrateDB vs. Datastax Enterprise vs. GridDB vs. IBM Db2 Event Store vs. Microsoft Access
System Properties Comparison CrateDB vs. Datastax Enterprise vs. GridDB vs. IBM Db2 Event Store vs. Microsoft Access
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Name | CrateDB Xexclude from comparison | Datastax Enterprise Xexclude from comparison | GridDB Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | Microsoft Access Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform. | Scalable in-memory time series database optimized for IoT and Big Data | Distributed Event Store optimized for Internet of Things use cases | Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Wide column store | Time Series DBMS | Event Store Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Relational DBMS | Document store Graph DBMS Spatial DBMS Search engine Vector DBMS | Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | www.datastax.com/products/datastax-enterprise | griddb.net | www.ibm.com/products/db2-event-store | www.microsoft.com/en-us/microsoft-365/access | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | docs.datastax.com | docs.griddb.net | www.ibm.com/docs/en/db2-event-store | developer.microsoft.com/en-us/access | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | DataStax | Toshiba Corporation | IBM | Microsoft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2011 | 2013 | 2017 | 1992 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 6.8, April 2020 | 5.1, August 2022 | 2.0 | 1902 (16.0.11328.20222), March 2019 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | commercial | Open Source AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available | commercial free developer edition available | commercial Bundled with Microsoft Office | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | 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. | Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | Java | C++ | C and C++ | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux OS X | Linux | Linux Linux, macOS, Windows for the developer addition | Windows Not a real database server, but making use of DLLs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | schema-free | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | yes numerical, string, blob, geometry, boolean, timestamp | 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 | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | SQL-like DML and DDL statements (CQL); Spark SQL | SQL92, SQL-like TQL (Toshiba Query Language) | yes through the embedded Spark runtime | yes but not compliant to any SQL standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | Proprietary protocol CQL (Cassandra Query Language) TinkerPop Gremlin with DSE Graph | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | ADO.NET DAO ODBC OLE DB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | C C# C++ Java JavaScript (Node.js) PHP Python Ruby | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic | C C# C++ Delphi Java (JDBC-ODBC) VBA Visual Basic.NET | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | no | no | yes | yes since Access 2010 using the ACE-engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | yes | no | yes since Access 2010 using the ACE-engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding no "single point of failure" | Sharding | Sharding | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | configurable replication factor, datacenter aware, advanced replication for edge computing | Source-replica replication | Active-active shard replication | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Immediate Consistency Tunable Consistency consistency level can be individually decided with each write operation | Immediate consistency within container, eventual consistency across containers | Eventual Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | 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 | no Atomicity and isolation are supported for single operations | ACID at container level | no | ACID but no files for transaction logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | No - written data is immutable | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | yes but no files for transaction logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | Access rights for users can be defined per object | Access rights for users can be defined per database | fine grained access rights according to SQL-standard | no a simple user-level security was built in till version Access 2003 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | Datastax Enterprise | GridDB | IBM Db2 Event Store | Microsoft Access | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | DataStax Enterprise is scale-out data infrastructure for enterprises that need to... » more | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | Supporting the following application requirements: Zero downtime - Built on Apache... » more | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | Applications that must be massively and linearly scalable with 100% uptime and able... » more | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and... » more | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top... » more | GitHub trending repository » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | Annual subscription » more | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | Datastax Enterprise | GridDB | IBM Db2 Event Store | Microsoft Access | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | MS Access drops in DB-Engines Ranking Microsoft SQL Server regained rank 2 in the DB-Engines popularity ranking New DB-Engines Ranking shows the popularity of database management systems CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Announces Availability of CrateDB on Google Cloud Marketplace 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 provided by Google News DataStax and LlamaIndex Partner to Make Building RAG Applications Easier than Ever for GenAI Developers DataStax Introduces Enhanced RAG Capabilities Through Astra DB and NVIDIA Tech DataStax Rolls Out Vector Search for Astra DB to Support Gen AI DataStax adds vector search to boost support for generative AI workloads DataStax goes vector searching with Astra DB – Blocks and Files provided by Google News General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ... Toshiba launches cloudy managed IoT database service running its own GridDB GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ... Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ... General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ... provided by Google News Advancements in streaming data storage, real-time analysis and machine learning IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere How IBM Is Turning Db2 into an 'AI Database' Best cloud databases of 2022 Why a robust data management strategy is essential today | IBM HDM provided by Google News Abusing Microsoft Access "Linked Table" Feature to Perform NTLM Forced Authentication Attacks Hackers Exploit Microsoft Access Feature to Steal Windows User’s NTLM Tokens MS access program to increase awareness and independence of those living with MS and disability After installing Navisworks, Office 2016 (32-bit) applications stopped launching ACCDE File (What It Is and How to Open One) provided by Google News |
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