DBMS > Faircom DB vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Tarantool
System Properties Comparison Faircom DB vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Tarantool
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Name | Faircom DB formerly c-treeACE Xexclude from comparison | Hazelcast Xexclude from comparison | Ingres Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs. | A widely adopted in-memory data grid | Well established RDBMS | Fully managed big data interactive analytics platform | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Relational DBMS | Key-value store | Relational DBMS | Relational DBMS column oriented | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store JSON support with IMDG 3.12 | 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 | Spatial DBMS with Tarantool/GIS extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.faircom.com/products/faircom-db | hazelcast.com | www.actian.com/databases/ingres | azure.microsoft.com/services/data-explorer | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html | hazelcast.org/imdg/docs | docs.actian.com/ingres | docs.microsoft.com/en-us/azure/data-explorer | www.tarantool.io/en/doc | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | FairCom Corporation | Hazelcast | Actian Corporation | Microsoft | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 1979 | 2008 | 1974 originally developed at University Berkely in early 1970s | 2019 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | V12, November 2020 | 5.3.6, November 2023 | 11.2, May 2022 | cloud service with continuous releases | 2.10.0, May 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial Restricted, free version available | Open Source Apache Version 2; commercial licenses available | commercial | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | ANSI C, C++ | Java | C | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | AIX FreeBSD HP-UX Linux NetBSD OS X QNX SCO Solaris VxWorks Windows easily portable to other OSs | All OS with a Java VM | AIX HP Open VMS HP-UX Linux Solaris Windows | hosted | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema free, schema optional, schema required, partial schema, | schema-free | yes | Fixed schema with schema-less datatypes (dynamic) | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes, ANSI SQL Types, JSON, typed binary structures | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | string, double, decimal, uuid, integer, blob, boolean, datetime | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 the object must implement a serialization strategy | no but tools for importing/exporting data from/to XML-files available | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | all fields are automatically indexed | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, ANSI SQL with proprietary extensions | SQL-like query language | yes | Kusto Query Language (KQL), SQL subset | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET Direct SQL JDBC JPA ODBC RESTful HTTP/JSON API RESTful MQTT/JSON API RPC | JCache JPA Memcached protocol RESTful HTTP API | .NET Client API JDBC ODBC proprietary protocol (OpenAPI) | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C C# C++ Java JavaScript (Node.js and browser) PHP Python Visual Basic | .Net C# C++ Clojure Go Java JavaScript (Node.js) Python Scala | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes .Net, JavaScript, C/C++ | yes Event Listeners, Executor Services | yes | Yes, possible languages: KQL, Python, R | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | yes Events | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | File partitioning, horizontal partitioning, sharding Customizable business rules for table partitioning | Sharding | horizontal partitioning Ingres Star to access multiple databases simultaneously | Sharding Implicit feature of the cloud service | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution). | yes Replicated Map | Ingres Replicator | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | yes | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency Tunable consistency per server, database, table, and transaction | Immediate Consistency or Eventual Consistency selectable by user Raft Consensus Algorithm | Immediate Consistency | Eventual Consistency Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | tunable from ACID to Eventually Consistent | one or two-phase-commit; repeatable reads; read commited | ACID | no | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes MVCC | yes | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | Yes, tunable from durable to delayed durability to in-memory | yes | yes | yes | yes, write ahead logging | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | no | yes, full featured in-memory storage engine with persistence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Fine grained access rights according to SQL-standard with additional protections for files | Role-based access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and servicesWe invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Faircom DB formerly c-treeACE | Hazelcast | Ingres | Microsoft Azure Data Explorer | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Data processing speed and reliability: in-memory synchronous replication FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple' FairCom kicks off new era of database technology USA - English provided by Google News Hazelcast Weaves Wider Logic Threads Through The Data Fabric Hazelcast appoints Anthony Griffin as Chief Architect - Hazelcast 5.4 real time data processing platform boosts AI and consistency Hazelcast Achieves Record Year with Leading Brands Choosing Its Platform for Application Modernization, AI Initiatives Hazelcast Versus Redis: A Practical Comparison provided by Google News Actian Launches Ingres 12.0 Database Postgres pioneer Michael Stonebraker promises to upend the database once more New startup from Postgres creator puts the database at heart of software stack Actian Launches Ingres as a Fully-Managed Cloud Service Dr. Michael Stonebraker: A Short History of Database Systems provided by Google News We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities Deploying Tarantool Cartridge applications with zero effort (Part 1) VShard — horizontal scaling in Tarantool Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel provided by Google News |
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