DBMS > Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Tarantool vs. Vertica
System Properties Comparison Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Tarantool vs. Vertica
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| Name | Hazelcast Xexclude from comparison | Ingres Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Tarantool Xexclude from comparison | Vertica  OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | 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 | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Key-value store | Relational DBMS | Relational DBMS column oriented | Document store Key-value store Relational DBMS | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 engineTime Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS with Tarantool/GIS extension | Spatial DBMS Time Series DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | hazelcast.com | www.actian.com/databases/ingres | azure.microsoft.com/services/data-explorer | www.tarantool.io | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | hazelcast.org/imdg/docs | docs.actian.com/ingres | docs.microsoft.com/en-us/azure/data-explorer | www.tarantool.io/en/doc | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Hazelcast | Actian Corporation | Microsoft | VK | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2008 | 1974 originally developed at University Berkely in early 1970s | 2019 | 2008 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 5.3.6, November 2023 | 11.2, May 2022 | cloud service with continuous releases | 2.10.0, May 2022 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache Version 2; commercial licenses available | commercial | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | yes | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | Java | C | C and C++ | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | All OS with a Java VM | AIX HP Open VMS HP-UX Linux Solaris Windows | hosted | BSD Linux macOS | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | 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 | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | 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 | 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. | yes the object must implement a serialization strategy | no but tools for importing/exporting data from/to XML-files available | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | all fields are automatically indexed | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like query language | yes | Kusto Query Language (KQL), SQL subset | Full-featured ANSI SQL support | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | 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 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | .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 | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes Event Listeners, Executor Services | yes | Yes, possible languages: KQL, Python, R | Lua, C and SQL stored procedures | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | 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 | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | 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. | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | 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) | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no Bi-directional Spark integration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | 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 replicationImmediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | 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 | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes MVCC | yes | yes, cooperative multitasking | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes, write ahead logging | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | no | yes, full featured in-memory storage engine with persistence | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | 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 | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Hazelcast | Ingres | Microsoft Azure Data Explorer | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Hazelcast | Ingres | Microsoft Azure Data Explorer | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Data processing speed and reliability: in-memory synchronous replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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