DBMS > HEAVY.AI vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Sqrrl vs. Tarantool
System Properties Comparison HEAVY.AI vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Sqrrl vs. Tarantool
| Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Name | HEAVY.AI  Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Splice Machine Xexclude from comparison | Sqrrl Xexclude from comparison | Tarantool Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | Fully managed big data interactive analytics platform | Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark | Adaptable, secure NoSQL built on Apache Accumulo | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Relational DBMS column oriented | Relational DBMS | Document store Graph DBMS Key-value store Wide column store | Document store Key-value store Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Spatial DBMS | 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 engineTime 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 | github.com/heavyai/heavydb www.heavy.ai | azure.microsoft.com/services/data-explorer | splicemachine.com | sqrrl.com | www.tarantool.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.heavy.ai | docs.microsoft.com/en-us/azure/data-explorer | splicemachine.com/how-it-works | www.tarantool.io/en/doc | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | HEAVY.AI, Inc. | Microsoft | Splice Machine | Amazon originally Sqrrl Data, Inc. | VK | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2016 | 2019 | 2014 | 2012 | 2008 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 5.10, January 2022 | cloud service with continuous releases | 3.1, March 2021 | 2.10.0, May 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2; enterprise edition available | commercial | Open Source AGPL 3.0, commercial license available | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | C++ and CUDA | Java | Java | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux | hosted | Linux OS X Solaris Windows | Linux | BSD Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | Fixed schema with schema-less datatypes (dynamic) | yes | schema-free | 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 | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | yes | 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 | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | no | all fields are automatically indexed | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | Kusto Query Language (KQL), SQL subset | yes | no | Full-featured ANSI SQL support | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC Thrift Vega | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC Native Spark Datasource ODBC | Accumulo Shell Java API JDBC ODBC RESTful HTTP API Thrift | Open binary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | All languages supporting JDBC/ODBC/Thrift Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | C# C++ Java JavaScript (Node.js) Python R Scala | Actionscript C using GLibC# C++ Cocoa Delphi Erlang Go Haskell Java JavaScript OCaml Perl PHP Python Ruby Smalltalk | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | no | Yes, possible languages: KQL, Python, R | yes Java | no | Lua, C and SQL stored procedures | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | no | yes, before/after data modification events, on replication events, client session events | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding Round robin | Sharding Implicit feature of the cloud service | Shared Nothhing Auto-Sharding, Columnar Partitioning | Sharding making use of Hadoop | 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 | Multi-source replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Multi-source replication Source-replica replication | selectable replication factor making use of Hadoop | 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 | Spark connector (open source): github.com/Azure/azure-kusto-spark | Yes, via Full Spark Integration | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution. | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replicationImmediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no | ACID | Atomic updates per row, document, or graph entity | 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, multi-version concurrency control (MVCC) | yes | yes, cooperative multitasking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | 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 | no | yes | yes, full featured in-memory storage engine with persistence | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | Access rights for users, groups and roles according to SQL-standard | Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC) | 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, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Microsoft Azure Data Explorer | Splice Machine | Sqrrl | Tarantool | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Data processing speed and reliability: in-memory synchronous replication HEAVY.AI: The Fastest Analytics and Location Intelligence Platform Big Data Analytics: A Game Changer for Infrastructure HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks Making the most of geospatial intelligence 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 Machine learning data pipeline outfit Splice Machine files for insolvency Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ... Distributed SQL System Review: Snowflake vs Splice Machine Splice Machine Launches Feature Store to Simplify Feature Engineering Splice Machine scores $15M to make Hadoop run in real time provided by Google News Splunk details Sqrrl 'screw-ups' that hampered threat hunting Amazon's cloud business acquires Sqrrl, a security start-up with NSA roots Millennials possess the advantage of time for wealth creation, says Yashoraj Tyagi of Sqrrl | Mint AWS beefs up threat detection with Sqrrl acquisition Amazon acquires cybersecurity startup Sqrrl 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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